---
_id: '9647'
abstract:
- lang: eng
text: 'Gene expression is regulated by the set of transcription factors (TFs) that
bind to the promoter. The ensuing regulating function is often represented as
a combinational logic circuit, where output (gene expression) is determined by
current input values (promoter bound TFs) only. However, the simultaneous arrival
of TFs is a strong assumption, since transcription and translation of genes introduce
intrinsic time delays and there is no global synchronisation among the arrival
times of different molecular species at their targets. We present an experimentally
implementable genetic circuit with two inputs and one output, which in the presence
of small delays in input arrival, exhibits qualitatively distinct population-level
phenotypes, over timescales that are longer than typical cell doubling times.
From a dynamical systems point of view, these phenotypes represent long-lived
transients: although they converge to the same value eventually, they do so after
a very long time span. The key feature of this toy model genetic circuit is that,
despite having only two inputs and one output, it is regulated by twenty-three
distinct DNA-TF configurations, two of which are more stable than others (DNA
looped states), one promoting and another blocking the expression of the output
gene. Small delays in input arrival time result in a majority of cells in the
population quickly reaching the stable state associated with the first input,
while exiting of this stable state occurs at a slow timescale. In order to mechanistically
model the behaviour of this genetic circuit, we used a rule-based modelling language,
and implemented a grid-search to find parameter combinations giving rise to long-lived
transients. Our analysis shows that in the absence of feedback, there exist path-dependent
gene regulatory mechanisms based on the long timescale of transients. The behaviour
of this toy model circuit suggests that gene regulatory networks can exploit event
timing to create phenotypes, and it opens the possibility that they could use
event timing to memorise events, without regulatory feedback. The model reveals
the importance of (i) mechanistically modelling the transitions between the different
DNA-TF states, and (ii) employing transient analysis thereof.'
acknowledgement: 'Tatjana Petrov’s research was supported in part by SNSF Advanced
Postdoctoral Mobility Fellowship grant number P300P2 161067, the Ministry of Science,
Research and the Arts of the state of Baden-Wurttemberg, and the DFG Centre of Excellence
2117 ‘Centre for the Advanced Study of Collective Behaviour’ (ID: 422037984). Claudia
Igler is the recipient of a DOC Fellowship of the Austrian Academy of Sciences.
Thomas A. Henzinger’s research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award).'
article_processing_charge: No
article_type: original
author:
- first_name: Tatjana
full_name: Petrov, Tatjana
last_name: Petrov
- first_name: Claudia
full_name: Igler, Claudia
id: 46613666-F248-11E8-B48F-1D18A9856A87
last_name: Igler
- first_name: Ali
full_name: Sezgin, Ali
id: 4C7638DA-F248-11E8-B48F-1D18A9856A87
last_name: Sezgin
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Petrov T, Igler C, Sezgin A, Henzinger TA, Guet CC. Long lived transients in
gene regulation. Theoretical Computer Science. 2021;893:1-16. doi:10.1016/j.tcs.2021.05.023
apa: Petrov, T., Igler, C., Sezgin, A., Henzinger, T. A., & Guet, C. C. (2021).
Long lived transients in gene regulation. Theoretical Computer Science.
Elsevier. https://doi.org/10.1016/j.tcs.2021.05.023
chicago: Petrov, Tatjana, Claudia Igler, Ali Sezgin, Thomas A Henzinger, and Calin
C Guet. “Long Lived Transients in Gene Regulation.” Theoretical Computer Science.
Elsevier, 2021. https://doi.org/10.1016/j.tcs.2021.05.023.
ieee: T. Petrov, C. Igler, A. Sezgin, T. A. Henzinger, and C. C. Guet, “Long lived
transients in gene regulation,” Theoretical Computer Science, vol. 893.
Elsevier, pp. 1–16, 2021.
ista: Petrov T, Igler C, Sezgin A, Henzinger TA, Guet CC. 2021. Long lived transients
in gene regulation. Theoretical Computer Science. 893, 1–16.
mla: Petrov, Tatjana, et al. “Long Lived Transients in Gene Regulation.” Theoretical
Computer Science, vol. 893, Elsevier, 2021, pp. 1–16, doi:10.1016/j.tcs.2021.05.023.
short: T. Petrov, C. Igler, A. Sezgin, T.A. Henzinger, C.C. Guet, Theoretical Computer
Science 893 (2021) 1–16.
date_created: 2021-07-11T22:01:18Z
date_published: 2021-06-04T00:00:00Z
date_updated: 2023-08-10T14:11:19Z
day: '04'
ddc:
- '004'
department:
- _id: ToHe
- _id: CaGu
doi: 10.1016/j.tcs.2021.05.023
external_id:
isi:
- '000710180500002'
file:
- access_level: open_access
checksum: d3aef34cfb13e53bba4cf44d01680793
content_type: application/pdf
creator: dernst
date_created: 2022-05-12T12:13:27Z
date_updated: 2022-05-12T12:13:27Z
file_id: '11364'
file_name: 2021_TheoreticalComputerScience_Petrov.pdf
file_size: 2566504
relation: main_file
success: 1
file_date_updated: 2022-05-12T12:13:27Z
has_accepted_license: '1'
intvolume: ' 893'
isi: 1
language:
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license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '06'
oa: 1
oa_version: Published Version
page: 1-16
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Theoretical Computer Science
publication_identifier:
issn:
- 0304-3975
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Long lived transients in gene regulation
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 893
year: '2021'
...
---
_id: '10108'
abstract:
- lang: eng
text: We argue that the time is ripe to investigate differential monitoring, in
which the specification of a program's behavior is implicitly given by a second
program implementing the same informal specification. Similar ideas have been
proposed before, and are currently implemented in restricted form for testing
and specialized run-time analyses, aspects of which we combine. We discuss the
challenges of implementing differential monitoring as a general-purpose, black-box
run-time monitoring framework, and present promising results of a preliminary
implementation, showing low monitoring overheads for diverse programs.
acknowledgement: The authors would like to thank Borzoo Bonakdarpour, Derek Dreyer,
Adrian Francalanza, Owolabi Legunsen, Mae Milano, Manuel Rigger, Cesar Sanchez,
and the members of the IST Verification Seminar for their helpful comments and insights
on various stages of this work, as well as the reviewers of RV’21 for their helpful
suggestions on the actual paper.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Fabian
full_name: Mühlböck, Fabian
id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425
last_name: Mühlböck
orcid: 0000-0003-1548-0177
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Mühlböck F, Henzinger TA. Differential monitoring. In: International Conference
on Runtime Verification. Vol 12974. Cham: Springer Nature; 2021:231-243. doi:10.1007/978-3-030-88494-9_12'
apa: 'Mühlböck, F., & Henzinger, T. A. (2021). Differential monitoring. In International
Conference on Runtime Verification (Vol. 12974, pp. 231–243). Cham: Springer
Nature. https://doi.org/10.1007/978-3-030-88494-9_12'
chicago: 'Mühlböck, Fabian, and Thomas A Henzinger. “Differential Monitoring.” In
International Conference on Runtime Verification, 12974:231–43. Cham: Springer
Nature, 2021. https://doi.org/10.1007/978-3-030-88494-9_12.'
ieee: F. Mühlböck and T. A. Henzinger, “Differential monitoring,” in International
Conference on Runtime Verification, Virtual, 2021, vol. 12974, pp. 231–243.
ista: 'Mühlböck F, Henzinger TA. 2021. Differential monitoring. International Conference
on Runtime Verification. RV: Runtime Verification, LNCS, vol. 12974, 231–243.'
mla: Mühlböck, Fabian, and Thomas A. Henzinger. “Differential Monitoring.” International
Conference on Runtime Verification, vol. 12974, Springer Nature, 2021, pp.
231–43, doi:10.1007/978-3-030-88494-9_12.
short: F. Mühlböck, T.A. Henzinger, in:, International Conference on Runtime Verification,
Springer Nature, Cham, 2021, pp. 231–243.
conference:
end_date: 2021-10-14
location: Virtual
name: 'RV: Runtime Verification'
start_date: 2021-10-11
date_created: 2021-10-07T23:30:10Z
date_published: 2021-10-06T00:00:00Z
date_updated: 2023-08-14T07:20:30Z
day: '06'
ddc:
- '005'
department:
- _id: ToHe
doi: 10.1007/978-3-030-88494-9_12
external_id:
isi:
- '000719383800012'
file:
- access_level: open_access
checksum: 554c7fdb259eda703a8b6328a6dad55a
content_type: application/pdf
creator: fmuehlbo
date_created: 2021-10-07T23:32:18Z
date_updated: 2021-10-07T23:32:18Z
file_id: '10109'
file_name: differentialmonitoring-cameraready-openaccess.pdf
file_size: 350632
relation: main_file
success: 1
file_date_updated: 2021-10-07T23:32:18Z
has_accepted_license: '1'
intvolume: ' 12974'
isi: 1
keyword:
- run-time verification
- software engineering
- implicit specification
language:
- iso: eng
month: '10'
oa: 1
oa_version: Preprint
page: 231-243
place: Cham
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: International Conference on Runtime Verification
publication_identifier:
eisbn:
- 978-3-030-88494-9
eissn:
- 1611-3349
isbn:
- 978-3-030-88493-2
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '9946'
relation: extended_version
status: public
scopus_import: '1'
status: public
title: Differential monitoring
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 12974
year: '2021'
...
---
_id: '9946'
abstract:
- lang: eng
text: We argue that the time is ripe to investigate differential monitoring, in
which the specification of a program's behavior is implicitly given by a second
program implementing the same informal specification. Similar ideas have been
proposed before, and are currently implemented in restricted form for testing
and specialized run-time analyses, aspects of which we combine. We discuss the
challenges of implementing differential monitoring as a general-purpose, black-box
run-time monitoring framework, and present promising results of a preliminary
implementation, showing low monitoring overheads for diverse programs.
acknowledgement: The authors would like to thank Borzoo Bonakdarpour, Derek Dreyer,
Adrian Francalanza, Owolabi Legunsen, Matthew Milano, Manuel Rigger, Cesar Sanchez,
and the members of the IST Verification Seminar for their helpful comments and insights
on various stages of this work, as well as the reviewers of RV’21 for their helpful
suggestions on the actual paper.
alternative_title:
- IST Austria Technical Report
article_processing_charge: No
author:
- first_name: Fabian
full_name: Mühlböck, Fabian
id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425
last_name: Mühlböck
orcid: 0000-0003-1548-0177
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Mühlböck F, Henzinger TA. Differential Monitoring. IST Austria; 2021.
doi:10.15479/AT:ISTA:9946
apa: Mühlböck, F., & Henzinger, T. A. (2021). Differential monitoring.
IST Austria. https://doi.org/10.15479/AT:ISTA:9946
chicago: Mühlböck, Fabian, and Thomas A Henzinger. Differential Monitoring.
IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:9946.
ieee: F. Mühlböck and T. A. Henzinger, Differential monitoring. IST Austria,
2021.
ista: Mühlböck F, Henzinger TA. 2021. Differential monitoring, IST Austria, 17p.
mla: Mühlböck, Fabian, and Thomas A. Henzinger. Differential Monitoring.
IST Austria, 2021, doi:10.15479/AT:ISTA:9946.
short: F. Mühlböck, T.A. Henzinger, Differential Monitoring, IST Austria, 2021.
date_created: 2021-08-20T20:00:37Z
date_published: 2021-09-01T00:00:00Z
date_updated: 2023-08-14T07:20:29Z
day: '01'
ddc:
- '005'
department:
- _id: ToHe
doi: 10.15479/AT:ISTA:9946
file:
- access_level: open_access
checksum: 0f9aafd59444cb6bdca6925d163ab946
content_type: application/pdf
creator: fmuehlbo
date_created: 2021-08-20T19:59:44Z
date_updated: 2021-09-03T12:34:28Z
file_id: '9948'
file_name: differentialmonitoring-techreport.pdf
file_size: '320453'
relation: main_file
file_date_updated: 2021-09-03T12:34:28Z
has_accepted_license: '1'
keyword:
- run-time verification
- software engineering
- implicit specification
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: '17'
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication_identifier:
issn:
- 2664-1690
publication_status: published
publisher: IST Austria
related_material:
record:
- id: '9281'
relation: other
status: public
- id: '10108'
relation: shorter_version
status: public
status: public
title: Differential monitoring
type: technical_report
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10404'
abstract:
- lang: eng
text: While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art
models for image-related tasks, their predictions are often highly sensitive to
small input perturbations, which the human vision is robust against. This paper
presents Perturber, a web-based application that allows users to instantaneously
explore how CNN activations and predictions evolve when a 3D input scene is interactively
perturbed. Perturber offers a large variety of scene modifications, such as camera
controls, lighting and shading effects, background modifications, object morphing,
as well as adversarial attacks, to facilitate the discovery of potential vulnerabilities.
Fine-tuned model versions can be directly compared for qualitative evaluation
of their robustness. Case studies with machine learning experts have shown that
Perturber helps users to quickly generate hypotheses about model vulnerabilities
and to qualitatively compare model behavior. Using quantitative analyses, we could
replicate users’ insights with other CNN architectures and input images, yielding
new insights about the vulnerability of adversarially trained models.
acknowledgement: "We thank Robert Geirhos and Roland Zimmermann for their participation
in the case study and valuable feedback, Chris Olah and Nick Cammarata for valuable
discussions in the early phase of the project, as well as the Distill Slack workspace
as a platform for discussions. M.L. is supported in part by the Austrian Science
Fund (FWF) under grant Z211-N23 (Wittgenstein Award). J.B. is supported by the German
Federal Ministry of Education and Research\r\n(BMBF) through the Competence Center
for Machine Learning (TUE.AI, FKZ 01IS18039A) and the International Max Planck Research
School for Intelligent Systems (IMPRS-IS). R.H. is partially supported by Boeing
and Horizon-2020 ECSEL (grant 783163, iDev40).\r\n"
article_processing_charge: No
article_type: original
author:
- first_name: Stefan
full_name: Sietzen, Stefan
last_name: Sietzen
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Judy
full_name: Borowski, Judy
last_name: Borowski
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Manuela
full_name: Waldner, Manuela
last_name: Waldner
citation:
ama: Sietzen S, Lechner M, Borowski J, Hasani R, Waldner M. Interactive analysis
of CNN robustness. Computer Graphics Forum. 2021;40(7):253-264. doi:10.1111/cgf.14418
apa: Sietzen, S., Lechner, M., Borowski, J., Hasani, R., & Waldner, M. (2021).
Interactive analysis of CNN robustness. Computer Graphics Forum. Wiley.
https://doi.org/10.1111/cgf.14418
chicago: Sietzen, Stefan, Mathias Lechner, Judy Borowski, Ramin Hasani, and Manuela
Waldner. “Interactive Analysis of CNN Robustness.” Computer Graphics Forum.
Wiley, 2021. https://doi.org/10.1111/cgf.14418.
ieee: S. Sietzen, M. Lechner, J. Borowski, R. Hasani, and M. Waldner, “Interactive
analysis of CNN robustness,” Computer Graphics Forum, vol. 40, no. 7. Wiley,
pp. 253–264, 2021.
ista: Sietzen S, Lechner M, Borowski J, Hasani R, Waldner M. 2021. Interactive analysis
of CNN robustness. Computer Graphics Forum. 40(7), 253–264.
mla: Sietzen, Stefan, et al. “Interactive Analysis of CNN Robustness.” Computer
Graphics Forum, vol. 40, no. 7, Wiley, 2021, pp. 253–64, doi:10.1111/cgf.14418.
short: S. Sietzen, M. Lechner, J. Borowski, R. Hasani, M. Waldner, Computer Graphics
Forum 40 (2021) 253–264.
date_created: 2021-12-05T23:01:40Z
date_published: 2021-11-27T00:00:00Z
date_updated: 2023-08-14T13:11:42Z
day: '27'
department:
- _id: ToHe
doi: 10.1111/cgf.14418
external_id:
arxiv:
- '2110.07667'
isi:
- '000722952000024'
intvolume: ' 40'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2110.07667
month: '11'
oa: 1
oa_version: Preprint
page: 253-264
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Computer Graphics Forum
publication_identifier:
eissn:
- 1467-8659
issn:
- 0167-7055
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Interactive analysis of CNN robustness
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 40
year: '2021'
...
---
_id: '10674'
abstract:
- lang: eng
text: 'In two-player games on graphs, the players move a token through a graph to
produce an infinite path, which determines the winner of the game. Such games
are central in formal methods since they model the interaction between a non-terminating
system and its environment. In bidding games the players bid for the right to
move the token: in each round, the players simultaneously submit bids, and the
higher bidder moves the token and pays the other player. Bidding games are known
to have a clean and elegant mathematical structure that relies on the ability
of the players to submit arbitrarily small bids. Many applications, however, require
a fixed granularity for the bids, which can represent, for example, the monetary
value expressed in cents. We study, for the first time, the combination of discrete-bidding
and infinite-duration games. Our most important result proves that these games
form a large determined subclass of concurrent games, where determinacy is the
strong property that there always exists exactly one player who can guarantee
winning the game. In particular, we show that, in contrast to non-discrete bidding
games, the mechanism with which tied bids are resolved plays an important role
in discrete-bidding games. We study several natural tie-breaking mechanisms and
show that, while some do not admit determinacy, most natural mechanisms imply
determinacy for every pair of initial budgets.'
acknowledgement: "This research was supported in part by the Austrian Science Fund
(FWF) under grants S11402-N23 (RiSE/SHiNE), Z211-N23 (Wittgenstein Award), and M
2369-N33 (Meitner fellowship).\r\n"
article_processing_charge: No
article_type: original
author:
- first_name: Milad
full_name: Aghajohari, Milad
last_name: Aghajohari
- first_name: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Aghajohari M, Avni G, Henzinger TA. Determinacy in discrete-bidding infinite-duration
games. Logical Methods in Computer Science. 2021;17(1):10:1-10:23. doi:10.23638/LMCS-17(1:10)2021
apa: Aghajohari, M., Avni, G., & Henzinger, T. A. (2021). Determinacy in discrete-bidding
infinite-duration games. Logical Methods in Computer Science. International
Federation for Computational Logic. https://doi.org/10.23638/LMCS-17(1:10)2021
chicago: Aghajohari, Milad, Guy Avni, and Thomas A Henzinger. “Determinacy in Discrete-Bidding
Infinite-Duration Games.” Logical Methods in Computer Science. International
Federation for Computational Logic, 2021. https://doi.org/10.23638/LMCS-17(1:10)2021.
ieee: M. Aghajohari, G. Avni, and T. A. Henzinger, “Determinacy in discrete-bidding
infinite-duration games,” Logical Methods in Computer Science, vol. 17,
no. 1. International Federation for Computational Logic, p. 10:1-10:23, 2021.
ista: Aghajohari M, Avni G, Henzinger TA. 2021. Determinacy in discrete-bidding
infinite-duration games. Logical Methods in Computer Science. 17(1), 10:1-10:23.
mla: Aghajohari, Milad, et al. “Determinacy in Discrete-Bidding Infinite-Duration
Games.” Logical Methods in Computer Science, vol. 17, no. 1, International
Federation for Computational Logic, 2021, p. 10:1-10:23, doi:10.23638/LMCS-17(1:10)2021.
short: M. Aghajohari, G. Avni, T.A. Henzinger, Logical Methods in Computer Science
17 (2021) 10:1-10:23.
date_created: 2022-01-25T16:32:13Z
date_published: 2021-02-03T00:00:00Z
date_updated: 2023-08-17T06:56:42Z
day: '03'
ddc:
- '510'
department:
- _id: ToHe
doi: 10.23638/LMCS-17(1:10)2021
external_id:
arxiv:
- '1905.03588'
isi:
- '000658724600010'
file:
- access_level: open_access
checksum: b35586a50ed1ca8f44767de116d18d81
content_type: application/pdf
creator: alisjak
date_created: 2022-01-26T08:04:50Z
date_updated: 2022-01-26T08:04:50Z
file_id: '10690'
file_name: 2021_LMCS_AGHAJOHAR.pdf
file_size: 819878
relation: main_file
success: 1
file_date_updated: 2022-01-26T08:04:50Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
issue: '1'
keyword:
- computer science
- computer science and game theory
- logic in computer science
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 10:1-10:23
project:
- _id: 264B3912-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02369
name: Formal Methods meets Algorithmic Game Theory
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Logical Methods in Computer Science
publication_identifier:
eissn:
- 1860-5974
publication_status: published
publisher: International Federation for Computational Logic
quality_controlled: '1'
scopus_import: '1'
status: public
title: Determinacy in discrete-bidding infinite-duration games
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 17
year: '2021'
...
---
_id: '10666'
abstract:
- lang: eng
text: Adversarial training is an effective method to train deep learning models
that are resilient to norm-bounded perturbations, with the cost of nominal performance
drop. While adversarial training appears to enhance the robustness and safety
of a deep model deployed in open-world decision-critical applications, counterintuitively,
it induces undesired behaviors in robot learning settings. In this paper, we show
theoretically and experimentally that neural controllers obtained via adversarial
training are subjected to three types of defects, namely transient, systematic,
and conditional errors. We first generalize adversarial training to a safety-domain
optimization scheme allowing for more generic specifications. We then prove that
such a learning process tends to cause certain error profiles. We support our
theoretical results by a thorough experimental safety analysis in a robot-learning
task. Our results suggest that adversarial training is not yet ready for robot
learning.
acknowledgement: M.L. and T.A.H. are supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by
Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40).
article_processing_charge: No
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is
not ready for robot learning. In: 2021 IEEE International Conference on Robotics
and Automation. ICRA. ; 2021:4140-4147. doi:10.1109/ICRA48506.2021.9561036'
apa: Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021).
Adversarial training is not ready for robot learning. In 2021 IEEE International
Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China. https://doi.org/10.1109/ICRA48506.2021.9561036
chicago: Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger.
“Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International
Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036.
ieee: M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial
training is not ready for robot learning,” in 2021 IEEE International Conference
on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147.
ista: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training
is not ready for robot learning. 2021 IEEE International Conference on Robotics
and Automation. ICRA: International Conference on Robotics and AutomationICRA,
4140–4147.'
mla: Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.”
2021 IEEE International Conference on Robotics and Automation, 2021, pp.
4140–47, doi:10.1109/ICRA48506.2021.9561036.
short: M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International
Conference on Robotics and Automation, 2021, pp. 4140–4147.
conference:
end_date: 2021-06-05
location: Xi'an, China
name: 'ICRA: International Conference on Robotics and Automation'
start_date: 2021-05-30
date_created: 2022-01-25T15:44:54Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2023-08-17T06:58:38Z
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
doi: 10.1109/ICRA48506.2021.9561036
external_id:
arxiv:
- '2103.08187'
isi:
- '000765738803040'
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/3.0/
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2103.08187
oa: 1
oa_version: None
page: 4140-4147
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 2021 IEEE International Conference on Robotics and Automation
publication_identifier:
eisbn:
- 978-1-7281-9077-8
eissn:
- 2577-087X
isbn:
- 978-1-7281-9078-5
issn:
- 1050-4729
publication_status: published
quality_controlled: '1'
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
series_title: ICRA
status: public
title: Adversarial training is not ready for robot learning
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...
---
_id: '10206'
abstract:
- lang: eng
text: Neural-network classifiers achieve high accuracy when predicting the class
of an input that they were trained to identify. Maintaining this accuracy in dynamic
environments, where inputs frequently fall outside the fixed set of initially
known classes, remains a challenge. The typical approach is to detect inputs from
novel classes and retrain the classifier on an augmented dataset. However, not
only the classifier but also the detection mechanism needs to adapt in order to
distinguish between newly learned and yet unknown input classes. To address this
challenge, we introduce an algorithmic framework for active monitoring of a neural
network. A monitor wrapped in our framework operates in parallel with the neural
network and interacts with a human user via a series of interpretable labeling
queries for incremental adaptation. In addition, we propose an adaptive quantitative
monitor to improve precision. An experimental evaluation on a diverse set of benchmarks
with varying numbers of classes confirms the benefits of our active monitoring
framework in dynamic scenarios.
acknowledgement: We thank Christoph Lampert and Alex Greengold for fruitful discussions.
This research was supported in part by the Simons Institute for the Theory of Computing,
the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), and the
European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie grant agreement No. 754411.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Anna
full_name: Lukina, Anna
id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425
last_name: Lukina
- first_name: Christian
full_name: Schilling, Christian
id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87
last_name: Schilling
orcid: 0000-0003-3658-1065
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Lukina A, Schilling C, Henzinger TA. Into the unknown: active monitoring of neural
networks. In: 21st International Conference on Runtime Verification. Vol
12974. Cham: Springer Nature; 2021:42-61. doi:10.1007/978-3-030-88494-9_3'
apa: 'Lukina, A., Schilling, C., & Henzinger, T. A. (2021). Into the unknown:
active monitoring of neural networks. In 21st International Conference on Runtime
Verification (Vol. 12974, pp. 42–61). Cham: Springer Nature. https://doi.org/10.1007/978-3-030-88494-9_3'
chicago: 'Lukina, Anna, Christian Schilling, and Thomas A Henzinger. “Into the Unknown:
Active Monitoring of Neural Networks.” In 21st International Conference on
Runtime Verification, 12974:42–61. Cham: Springer Nature, 2021. https://doi.org/10.1007/978-3-030-88494-9_3.'
ieee: 'A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown: active monitoring
of neural networks,” in 21st International Conference on Runtime Verification,
Virtual, 2021, vol. 12974, pp. 42–61.'
ista: 'Lukina A, Schilling C, Henzinger TA. 2021. Into the unknown: active monitoring
of neural networks. 21st International Conference on Runtime Verification. RV:
Runtime Verification, LNCS, vol. 12974, 42–61.'
mla: 'Lukina, Anna, et al. “Into the Unknown: Active Monitoring of Neural Networks.”
21st International Conference on Runtime Verification, vol. 12974, Springer
Nature, 2021, pp. 42–61, doi:10.1007/978-3-030-88494-9_3.'
short: A. Lukina, C. Schilling, T.A. Henzinger, in:, 21st International Conference
on Runtime Verification, Springer Nature, Cham, 2021, pp. 42–61.
conference:
end_date: 2021-10-14
location: Virtual
name: 'RV: Runtime Verification'
start_date: 2021-10-11
date_created: 2021-10-31T23:01:31Z
date_published: 2021-10-06T00:00:00Z
date_updated: 2024-01-30T12:06:56Z
day: '06'
department:
- _id: ToHe
doi: 10.1007/978-3-030-88494-9_3
ec_funded: 1
external_id:
arxiv:
- '2009.06429'
isi:
- '000719383800003'
isi: 1
keyword:
- monitoring
- neural networks
- novelty detection
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2009.06429
month: '10'
oa: 1
oa_version: Preprint
page: 42-61
place: Cham
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 21st International Conference on Runtime Verification
publication_identifier:
eisbn:
- 978-3-030-88494-9
eissn:
- 1611-3349
isbn:
- 9-783-0308-8493-2
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13234'
relation: extended_version
status: public
scopus_import: '1'
status: public
title: 'Into the unknown: active monitoring of neural networks'
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: '12974 '
year: '2021'
...
---
_id: '10673'
abstract:
- lang: eng
text: We propose a neural information processing system obtained by re-purposing
the function of a biological neural circuit model to govern simulated and real-world
control tasks. Inspired by the structure of the nervous system of the soil-worm,
C. elegans, we introduce ordinary neural circuits (ONCs), defined as the model
of biological neural circuits reparameterized for the control of alternative tasks.
We first demonstrate that ONCs realize networks with higher maximum flow compared
to arbitrary wired networks. We then learn instances of ONCs to control a series
of robotic tasks, including the autonomous parking of a real-world rover robot.
For reconfiguration of the purpose of the neural circuit, we adopt a search-based
optimization algorithm. Ordinary neural circuits perform on par and, in some cases,
significantly surpass the performance of contemporary deep learning models. ONC
networks are compact, 77% sparser than their counterpart neural controllers, and
their neural dynamics are fully interpretable at the cell-level.
acknowledgement: "RH and RG are partially supported by Horizon-2020 ECSEL Project
grant No. 783163 (iDev40), Productive 4.0, and ATBMBFW CPS-IoT Ecosystem. ML was
supported in part by the Austrian Science Fund (FWF) under grant Z211-N23\r\n(Wittgenstein
Award). AA is supported by the National Science Foundation (NSF) Graduate Research
Fellowship\r\nProgram. RH and DR are partially supported by The Boeing Company and
JP Morgan Chase. This research work is\r\npartially drawn from the PhD dissertation
of RH.\r\n"
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Alexander
full_name: Amini, Alexander
last_name: Amini
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
citation:
ama: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. A natural lottery ticket winner:
Reinforcement learning with ordinary neural circuits. In: Proceedings of the
37th International Conference on Machine Learning. PMLR. ; 2020:4082-4093.'
apa: 'Hasani, R., Lechner, M., Amini, A., Rus, D., & Grosu, R. (2020). A natural
lottery ticket winner: Reinforcement learning with ordinary neural circuits. In
Proceedings of the 37th International Conference on Machine Learning (pp.
4082–4093). Virtual.'
chicago: 'Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu
Grosu. “A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary
Neural Circuits.” In Proceedings of the 37th International Conference on Machine
Learning, 4082–93. PMLR, 2020.'
ieee: 'R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “A natural lottery
ticket winner: Reinforcement learning with ordinary neural circuits,” in Proceedings
of the 37th International Conference on Machine Learning, Virtual, 2020, pp.
4082–4093.'
ista: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. 2020. A natural lottery ticket
winner: Reinforcement learning with ordinary neural circuits. Proceedings of the
37th International Conference on Machine Learning. ML: Machine LearningPMLR, PMLR,
, 4082–4093.'
mla: 'Hasani, Ramin, et al. “A Natural Lottery Ticket Winner: Reinforcement Learning
with Ordinary Neural Circuits.” Proceedings of the 37th International Conference
on Machine Learning, 2020, pp. 4082–93.'
short: R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the
37th International Conference on Machine Learning, 2020, pp. 4082–4093.
conference:
end_date: 2020-07-18
location: Virtual
name: 'ML: Machine Learning'
start_date: 2020-07-12
date_created: 2022-01-25T15:50:34Z
date_published: 2020-01-01T00:00:00Z
date_updated: 2022-01-26T11:14:27Z
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
file:
- access_level: open_access
checksum: c9a4a29161777fc1a89ef451c040e3b1
content_type: application/pdf
creator: cchlebak
date_created: 2022-01-26T11:08:51Z
date_updated: 2022-01-26T11:08:51Z
file_id: '10691'
file_name: 2020_PMLR_Hasani.pdf
file_size: 2329798
relation: main_file
success: 1
file_date_updated: 2022-01-26T11:08:51Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://proceedings.mlr.press/v119/hasani20a.html
oa: 1
oa_version: Published Version
page: 4082-4093
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the 37th International Conference on Machine Learning
publication_identifier:
issn:
- 2640-3498
publication_status: published
quality_controlled: '1'
scopus_import: '1'
series_title: PMLR
status: public
title: 'A natural lottery ticket winner: Reinforcement learning with ordinary neural
circuits'
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2020'
...
---
_id: '7348'
abstract:
- lang: eng
text: 'The monitoring of event frequencies can be used to recognize behavioral anomalies,
to identify trends, and to deduce or discard hypotheses about the underlying system.
For example, the performance of a web server may be monitored based on the ratio
of the total count of requests from the least and most active clients. Exact frequency
monitoring, however, can be prohibitively expensive; in the above example it would
require as many counters as there are clients. In this paper, we propose the efficient
probabilistic monitoring of common frequency properties, including the mode (i.e.,
the most common event) and the median of an event sequence. We define a logic
to express composite frequency properties as a combination of atomic frequency
properties. Our main contribution is an algorithm that, under suitable probabilistic
assumptions, can be used to monitor these important frequency properties with
four counters, independent of the number of different events. Our algorithm samples
longer and longer subwords of an infinite event sequence. We prove the almost-sure
convergence of our algorithm by generalizing ergodic theory from increasing-length
prefixes to increasing-length subwords of an infinite sequence. A similar algorithm
could be used to learn a connected Markov chain of a given structure from observing
its outputs, to arbitrary precision, for a given confidence. '
alternative_title:
- LIPIcs
article_number: '20'
article_processing_charge: No
author:
- first_name: Thomas
full_name: Ferrere, Thomas
id: 40960E6E-F248-11E8-B48F-1D18A9856A87
last_name: Ferrere
orcid: 0000-0001-5199-3143
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000−0002−2985−7724
- first_name: Bernhard
full_name: Kragl, Bernhard
id: 320FC952-F248-11E8-B48F-1D18A9856A87
last_name: Kragl
orcid: 0000-0001-7745-9117
citation:
ama: 'Ferrere T, Henzinger TA, Kragl B. Monitoring event frequencies. In: 28th
EACSL Annual Conference on Computer Science Logic. Vol 152. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik; 2020. doi:10.4230/LIPIcs.CSL.2020.20'
apa: 'Ferrere, T., Henzinger, T. A., & Kragl, B. (2020). Monitoring event frequencies.
In 28th EACSL Annual Conference on Computer Science Logic (Vol. 152). Barcelona,
Spain: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CSL.2020.20'
chicago: Ferrere, Thomas, Thomas A Henzinger, and Bernhard Kragl. “Monitoring Event
Frequencies.” In 28th EACSL Annual Conference on Computer Science Logic,
Vol. 152. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.CSL.2020.20.
ieee: T. Ferrere, T. A. Henzinger, and B. Kragl, “Monitoring event frequencies,”
in 28th EACSL Annual Conference on Computer Science Logic, Barcelona, Spain,
2020, vol. 152.
ista: 'Ferrere T, Henzinger TA, Kragl B. 2020. Monitoring event frequencies. 28th
EACSL Annual Conference on Computer Science Logic. CSL: Computer Science Logic,
LIPIcs, vol. 152, 20.'
mla: Ferrere, Thomas, et al. “Monitoring Event Frequencies.” 28th EACSL Annual
Conference on Computer Science Logic, vol. 152, 20, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2020, doi:10.4230/LIPIcs.CSL.2020.20.
short: T. Ferrere, T.A. Henzinger, B. Kragl, in:, 28th EACSL Annual Conference on
Computer Science Logic, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
conference:
end_date: 2020-01-16
location: Barcelona, Spain
name: 'CSL: Computer Science Logic'
start_date: 2020-01-13
date_created: 2020-01-21T11:22:21Z
date_published: 2020-01-15T00:00:00Z
date_updated: 2021-01-12T08:13:12Z
day: '15'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.4230/LIPIcs.CSL.2020.20
external_id:
arxiv:
- '1910.06097'
file:
- access_level: open_access
checksum: b9a691d658d075c6369d3304d17fb818
content_type: application/pdf
creator: bkragl
date_created: 2020-01-21T11:21:04Z
date_updated: 2020-07-14T12:47:56Z
file_id: '7349'
file_name: main.pdf
file_size: 617206
relation: main_file
file_date_updated: 2020-07-14T12:47:56Z
has_accepted_license: '1'
intvolume: ' 152'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
project:
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 28th EACSL Annual Conference on Computer Science Logic
publication_identifier:
isbn:
- '9783959771320'
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: 1
status: public
title: Monitoring event frequencies
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 152
year: '2020'
...
---
_id: '8572'
abstract:
- lang: eng
text: 'We present the results of the ARCH 2020 friendly competition for formal verification
of continuous and hybrid systems with linear continuous dynamics. In its fourth
edition, eight tools have been applied to solve eight different benchmark problems
in the category for linear continuous dynamics (in alphabetical order): CORA,
C2E2, HyDRA, Hylaa, Hylaa-Continuous, JuliaReach, SpaceEx, and XSpeed. This report
is a snapshot of the current landscape of tools and the types of benchmarks they
are particularly suited for. Due to the diversity of problems, we are not ranking
tools, yet the presented results provide one of the most complete assessments
of tools for the safety verification of continuous and hybrid systems with linear
continuous dynamics up to this date.'
acknowledgement: "The authors gratefully acknowledge financial support by the European
Commission project\r\njustITSELF under grant number 817629, by the Austrian Science
Fund (FWF) under grant\r\nZ211-N23 (Wittgenstein Award), by the European Union’s
Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie
grant agreement No. 754411, and by the\r\nScience and Engineering Research Board
(SERB) project with file number IMP/2018/000523.\r\nThis material is based upon
work supported by the Air Force Office of Scientific Research under\r\naward number
FA9550-19-1-0288. Any opinions, finding, and conclusions or recommendations\r\nexpressed
in this material are those of the author(s) and do not necessarily reflect the views
of\r\nthe United States Air Force."
article_processing_charge: No
author:
- first_name: Matthias
full_name: Althoff, Matthias
last_name: Althoff
- first_name: Stanley
full_name: Bak, Stanley
last_name: Bak
- first_name: Zongnan
full_name: Bao, Zongnan
last_name: Bao
- first_name: Marcelo
full_name: Forets, Marcelo
last_name: Forets
- first_name: Goran
full_name: Frehse, Goran
last_name: Frehse
- first_name: Daniel
full_name: Freire, Daniel
last_name: Freire
- first_name: Niklas
full_name: Kochdumper, Niklas
last_name: Kochdumper
- first_name: Yangge
full_name: Li, Yangge
last_name: Li
- first_name: Sayan
full_name: Mitra, Sayan
last_name: Mitra
- first_name: Rajarshi
full_name: Ray, Rajarshi
last_name: Ray
- first_name: Christian
full_name: Schilling, Christian
id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87
last_name: Schilling
orcid: 0000-0003-3658-1065
- first_name: Stefan
full_name: Schupp, Stefan
last_name: Schupp
- first_name: Mark
full_name: Wetzlinger, Mark
last_name: Wetzlinger
citation:
ama: 'Althoff M, Bak S, Bao Z, et al. ARCH-COMP20 Category Report: Continuous and
hybrid systems with linear dynamics. In: EPiC Series in Computing. Vol
74. EasyChair; 2020:16-48. doi:10.29007/7dt2'
apa: 'Althoff, M., Bak, S., Bao, Z., Forets, M., Frehse, G., Freire, D., … Wetzlinger,
M. (2020). ARCH-COMP20 Category Report: Continuous and hybrid systems with linear
dynamics. In EPiC Series in Computing (Vol. 74, pp. 16–48). EasyChair.
https://doi.org/10.29007/7dt2'
chicago: 'Althoff, Matthias, Stanley Bak, Zongnan Bao, Marcelo Forets, Goran Frehse,
Daniel Freire, Niklas Kochdumper, et al. “ARCH-COMP20 Category Report: Continuous
and Hybrid Systems with Linear Dynamics.” In EPiC Series in Computing,
74:16–48. EasyChair, 2020. https://doi.org/10.29007/7dt2.'
ieee: 'M. Althoff et al., “ARCH-COMP20 Category Report: Continuous and hybrid
systems with linear dynamics,” in EPiC Series in Computing, 2020, vol.
74, pp. 16–48.'
ista: 'Althoff M, Bak S, Bao Z, Forets M, Frehse G, Freire D, Kochdumper N, Li Y,
Mitra S, Ray R, Schilling C, Schupp S, Wetzlinger M. 2020. ARCH-COMP20 Category
Report: Continuous and hybrid systems with linear dynamics. EPiC Series in Computing.
ARCH: International Workshop on Applied Verification on Continuous and Hybrid
Systems vol. 74, 16–48.'
mla: 'Althoff, Matthias, et al. “ARCH-COMP20 Category Report: Continuous and Hybrid
Systems with Linear Dynamics.” EPiC Series in Computing, vol. 74, EasyChair,
2020, pp. 16–48, doi:10.29007/7dt2.'
short: M. Althoff, S. Bak, Z. Bao, M. Forets, G. Frehse, D. Freire, N. Kochdumper,
Y. Li, S. Mitra, R. Ray, C. Schilling, S. Schupp, M. Wetzlinger, in:, EPiC Series
in Computing, EasyChair, 2020, pp. 16–48.
conference:
end_date: 2020-07-12
name: 'ARCH: International Workshop on Applied Verification on Continuous and Hybrid
Systems'
start_date: 2020-07-12
date_created: 2020-09-26T14:49:43Z
date_published: 2020-09-25T00:00:00Z
date_updated: 2021-01-12T08:20:06Z
day: '25'
department:
- _id: ToHe
doi: 10.29007/7dt2
ec_funded: 1
intvolume: ' 74'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://easychair.org/publications/download/DRpS
month: '09'
oa: 1
oa_version: Published Version
page: 16-48
project:
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00312
name: The Wittgenstein Prize
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: EPiC Series in Computing
publication_status: published
publisher: EasyChair
quality_controlled: '1'
status: public
title: 'ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 74
year: '2020'
...
---
_id: '8571'
abstract:
- lang: eng
text: We present the results of a friendly competition for formal verification of
continuous and hybrid systems with nonlinear continuous dynamics. The friendly
competition took place as part of the workshop Applied Verification for Continuous
and Hybrid Systems (ARCH) in 2020. This year, 6 tools Ariadne, CORA, DynIbex,
Flow*, Isabelle/HOL, and JuliaReach (in alphabetic order) participated. These
tools are applied to solve reachability analysis problems on six benchmark problems,
two of them featuring hybrid dynamics. We do not rank the tools based on the results,
but show the current status and discover the potential advantages of different
tools.
acknowledgement: Christian Schilling acknowledges support in part by the Austrian
Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award) and the European Union’s
Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie
grant agreement No. 754411.
article_processing_charge: No
author:
- first_name: Luca
full_name: Geretti, Luca
last_name: Geretti
- first_name: Julien
full_name: Alexandre Dit Sandretto, Julien
last_name: Alexandre Dit Sandretto
- first_name: Matthias
full_name: Althoff, Matthias
last_name: Althoff
- first_name: Luis
full_name: Benet, Luis
last_name: Benet
- first_name: Alexandre
full_name: Chapoutot, Alexandre
last_name: Chapoutot
- first_name: Xin
full_name: Chen, Xin
last_name: Chen
- first_name: Pieter
full_name: Collins, Pieter
last_name: Collins
- first_name: Marcelo
full_name: Forets, Marcelo
last_name: Forets
- first_name: Daniel
full_name: Freire, Daniel
last_name: Freire
- first_name: Fabian
full_name: Immler, Fabian
last_name: Immler
- first_name: Niklas
full_name: Kochdumper, Niklas
last_name: Kochdumper
- first_name: David
full_name: Sanders, David
last_name: Sanders
- first_name: Christian
full_name: Schilling, Christian
id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87
last_name: Schilling
orcid: 0000-0003-3658-1065
citation:
ama: 'Geretti L, Alexandre Dit Sandretto J, Althoff M, et al. ARCH-COMP20 Category
Report: Continuous and hybrid systems with nonlinear dynamics. In: EPiC Series
in Computing. Vol 74. EasyChair; 2020:49-75. doi:10.29007/zkf6'
apa: 'Geretti, L., Alexandre Dit Sandretto, J., Althoff, M., Benet, L., Chapoutot,
A., Chen, X., … Schilling, C. (2020). ARCH-COMP20 Category Report: Continuous
and hybrid systems with nonlinear dynamics. In EPiC Series in Computing
(Vol. 74, pp. 49–75). EasyChair. https://doi.org/10.29007/zkf6'
chicago: 'Geretti, Luca, Julien Alexandre Dit Sandretto, Matthias Althoff, Luis
Benet, Alexandre Chapoutot, Xin Chen, Pieter Collins, et al. “ARCH-COMP20 Category
Report: Continuous and Hybrid Systems with Nonlinear Dynamics.” In EPiC Series
in Computing, 74:49–75. EasyChair, 2020. https://doi.org/10.29007/zkf6.'
ieee: 'L. Geretti et al., “ARCH-COMP20 Category Report: Continuous and hybrid
systems with nonlinear dynamics,” in EPiC Series in Computing, 2020, vol.
74, pp. 49–75.'
ista: 'Geretti L, Alexandre Dit Sandretto J, Althoff M, Benet L, Chapoutot A, Chen
X, Collins P, Forets M, Freire D, Immler F, Kochdumper N, Sanders D, Schilling
C. 2020. ARCH-COMP20 Category Report: Continuous and hybrid systems with nonlinear
dynamics. EPiC Series in Computing. ARCH: International Workshop on Applied Verification
on Continuous and Hybrid Systems vol. 74, 49–75.'
mla: 'Geretti, Luca, et al. “ARCH-COMP20 Category Report: Continuous and Hybrid
Systems with Nonlinear Dynamics.” EPiC Series in Computing, vol. 74, EasyChair,
2020, pp. 49–75, doi:10.29007/zkf6.'
short: L. Geretti, J. Alexandre Dit Sandretto, M. Althoff, L. Benet, A. Chapoutot,
X. Chen, P. Collins, M. Forets, D. Freire, F. Immler, N. Kochdumper, D. Sanders,
C. Schilling, in:, EPiC Series in Computing, EasyChair, 2020, pp. 49–75.
conference:
end_date: 2020-07-12
name: 'ARCH: International Workshop on Applied Verification on Continuous and Hybrid
Systems'
start_date: 2020-07-12
date_created: 2020-09-26T14:41:29Z
date_published: 2020-09-25T00:00:00Z
date_updated: 2021-01-12T08:20:06Z
day: '25'
department:
- _id: ToHe
doi: 10.29007/zkf6
ec_funded: 1
intvolume: ' 74'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://easychair.org/publications/download/nrdD
month: '09'
oa: 1
oa_version: Published Version
page: 49-75
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: EPiC Series in Computing
publication_status: published
publisher: EasyChair
quality_controlled: '1'
status: public
title: 'ARCH-COMP20 Category Report: Continuous and hybrid systems with nonlinear
dynamics'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 74
year: '2020'
...
---
_id: '8600'
abstract:
- lang: eng
text: 'A vector addition system with states (VASS) consists of a finite set of states
and counters. A transition changes the current state to the next state, and every
counter is either incremented, or decremented, or left unchanged. A state and
value for each counter is a configuration; and a computation is an infinite sequence
of configurations with transitions between successive configurations. A probabilistic
VASS consists of a VASS along with a probability distribution over the transitions
for each state. Qualitative properties such as state and configuration reachability
have been widely studied for VASS. In this work we consider multi-dimensional
long-run average objectives for VASS and probabilistic VASS. For a counter, the
cost of a configuration is the value of the counter; and the long-run average
value of a computation for the counter is the long-run average of the costs of
the configurations in the computation. The multi-dimensional long-run average
problem given a VASS and a threshold value for each counter, asks whether there
is a computation such that for each counter the long-run average value for the
counter does not exceed the respective threshold. For probabilistic VASS, instead
of the existence of a computation, we consider whether the expected long-run average
value for each counter does not exceed the respective threshold. Our main results
are as follows: we show that the multi-dimensional long-run average problem (a)
is NP-complete for integer-valued VASS; (b) is undecidable for natural-valued
VASS (i.e., nonnegative counters); and (c) can be solved in polynomial time for
probabilistic integer-valued VASS, and probabilistic natural-valued VASS when
all computations are non-terminating.'
alternative_title:
- LIPIcs
article_number: '23'
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Jan
full_name: Otop, Jan
id: 2FC5DA74-F248-11E8-B48F-1D18A9856A87
last_name: Otop
citation:
ama: 'Chatterjee K, Henzinger TA, Otop J. Multi-dimensional long-run average problems
for vector addition systems with states. In: 31st International Conference
on Concurrency Theory. Vol 171. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
2020. doi:10.4230/LIPIcs.CONCUR.2020.23'
apa: 'Chatterjee, K., Henzinger, T. A., & Otop, J. (2020). Multi-dimensional
long-run average problems for vector addition systems with states. In 31st
International Conference on Concurrency Theory (Vol. 171). Virtual: Schloss
Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2020.23'
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, and Jan Otop. “Multi-Dimensional
Long-Run Average Problems for Vector Addition Systems with States.” In 31st
International Conference on Concurrency Theory, Vol. 171. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.CONCUR.2020.23.
ieee: K. Chatterjee, T. A. Henzinger, and J. Otop, “Multi-dimensional long-run average
problems for vector addition systems with states,” in 31st International Conference
on Concurrency Theory, Virtual, 2020, vol. 171.
ista: 'Chatterjee K, Henzinger TA, Otop J. 2020. Multi-dimensional long-run average
problems for vector addition systems with states. 31st International Conference
on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol.
171, 23.'
mla: Chatterjee, Krishnendu, et al. “Multi-Dimensional Long-Run Average Problems
for Vector Addition Systems with States.” 31st International Conference on
Concurrency Theory, vol. 171, 23, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2020, doi:10.4230/LIPIcs.CONCUR.2020.23.
short: K. Chatterjee, T.A. Henzinger, J. Otop, in:, 31st International Conference
on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
conference:
end_date: 2020-09-04
location: Virtual
name: 'CONCUR: Conference on Concurrency Theory'
start_date: 2020-09-01
date_created: 2020-10-04T22:01:36Z
date_published: 2020-08-06T00:00:00Z
date_updated: 2021-01-12T08:20:15Z
day: '06'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.4230/LIPIcs.CONCUR.2020.23
external_id:
arxiv:
- '2007.08917'
file:
- access_level: open_access
checksum: 5039752f644c4b72b9361d21a5e31baf
content_type: application/pdf
creator: dernst
date_created: 2020-10-05T14:04:25Z
date_updated: 2020-10-05T14:04:25Z
file_id: '8610'
file_name: 2020_LIPIcsCONCUR_Chatterjee.pdf
file_size: 601231
relation: main_file
success: 1
file_date_updated: 2020-10-05T14:04:25Z
has_accepted_license: '1'
intvolume: ' 171'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 31st International Conference on Concurrency Theory
publication_identifier:
isbn:
- '9783959771603'
issn:
- '18688969'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multi-dimensional long-run average problems for vector addition systems with
states
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 171
year: '2020'
...
---
_id: '8599'
abstract:
- lang: eng
text: A graph game is a two-player zero-sum game in which the players move a token
throughout a graph to produce an infinite path, which determines the winner or
payoff of the game. In bidding games, both players have budgets, and in each turn,
we hold an "auction" (bidding) to determine which player moves the token. In this
survey, we consider several bidding mechanisms and study their effect on the properties
of the game. Specifically, bidding games, and in particular bidding games of infinite
duration, have an intriguing equivalence with random-turn games in which in each
turn, the player who moves is chosen randomly. We show how minor changes in the
bidding mechanism lead to unexpected differences in the equivalence with random-turn
games.
acknowledgement: We would like to thank all our collaborators Milad Aghajohari, Ventsislav
Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný, Josef Tkadlec, and Ðorđe
Žikelić; we hope the collaboration was as fun and meaningful for you as it was for
us.
alternative_title:
- LIPIcs
article_number: '2'
article_processing_charge: No
author:
- first_name: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Avni G, Henzinger TA. A survey of bidding games on graphs. In: 31st International
Conference on Concurrency Theory. Vol 171. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2020. doi:10.4230/LIPIcs.CONCUR.2020.2'
apa: 'Avni, G., & Henzinger, T. A. (2020). A survey of bidding games on graphs.
In 31st International Conference on Concurrency Theory (Vol. 171). Virtual:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2020.2'
chicago: Avni, Guy, and Thomas A Henzinger. “A Survey of Bidding Games on Graphs.”
In 31st International Conference on Concurrency Theory, Vol. 171. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.CONCUR.2020.2.
ieee: G. Avni and T. A. Henzinger, “A survey of bidding games on graphs,” in 31st
International Conference on Concurrency Theory, Virtual, 2020, vol. 171.
ista: 'Avni G, Henzinger TA. 2020. A survey of bidding games on graphs. 31st International
Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs,
vol. 171, 2.'
mla: Avni, Guy, and Thomas A. Henzinger. “A Survey of Bidding Games on Graphs.”
31st International Conference on Concurrency Theory, vol. 171, 2, Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2020, doi:10.4230/LIPIcs.CONCUR.2020.2.
short: G. Avni, T.A. Henzinger, in:, 31st International Conference on Concurrency
Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
conference:
end_date: 2020-09-04
location: Virtual
name: 'CONCUR: Conference on Concurrency Theory'
start_date: 2020-09-01
date_created: 2020-10-04T22:01:36Z
date_published: 2020-08-06T00:00:00Z
date_updated: 2021-01-12T08:20:13Z
day: '06'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.4230/LIPIcs.CONCUR.2020.2
file:
- access_level: open_access
checksum: 8f33b098e73724e0ac817f764d8e1a2d
content_type: application/pdf
creator: dernst
date_created: 2020-10-05T14:13:19Z
date_updated: 2020-10-05T14:13:19Z
file_id: '8611'
file_name: 2020_LIPIcsCONCUR_Avni.pdf
file_size: 868510
relation: main_file
success: 1
file_date_updated: 2020-10-05T14:13:19Z
has_accepted_license: '1'
intvolume: ' 171'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 31st International Conference on Concurrency Theory
publication_identifier:
isbn:
- '9783959771603'
issn:
- '18688969'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: A survey of bidding games on graphs
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 171
year: '2020'
...
---
_id: '9040'
abstract:
- lang: eng
text: Machine learning and formal methods have complimentary benefits and drawbacks.
In this work, we address the controller-design problem with a combination of techniques
from both fields. The use of black-box neural networks in deep reinforcement learning
(deep RL) poses a challenge for such a combination. Instead of reasoning formally
about the output of deep RL, which we call the wizard, we extract from it a decision-tree
based model, which we refer to as the magic book. Using the extracted model as
an intermediary, we are able to handle problems that are infeasible for either
deep RL or formal methods by themselves. First, we suggest, for the first time,
a synthesis procedure that is based on a magic book. We synthesize a stand-alone
correct-by-design controller that enjoys the favorable performance of RL. Second,
we incorporate a magic book in a bounded model checking (BMC) procedure. BMC allows
us to find numerous traces of the plant under the control of the wizard, which
a user can use to increase the trustworthiness of the wizard and direct further
training.
acknowledgement: This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award).
article_processing_charge: No
author:
- first_name: Par Alizadeh
full_name: Alamdari, Par Alizadeh
last_name: Alamdari
- first_name: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Anna
full_name: Lukina, Anna
id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425
last_name: Lukina
citation:
ama: 'Alamdari PA, Avni G, Henzinger TA, Lukina A. Formal methods with a touch of
magic. In: Proceedings of the 20th Conference on Formal Methods in Computer-Aided
Design. TU Wien Academic Press; 2020:138-147. doi:10.34727/2020/isbn.978-3-85448-042-6_21'
apa: 'Alamdari, P. A., Avni, G., Henzinger, T. A., & Lukina, A. (2020). Formal
methods with a touch of magic. In Proceedings of the 20th Conference on Formal
Methods in Computer-Aided Design (pp. 138–147). Online Conference: TU Wien
Academic Press. https://doi.org/10.34727/2020/isbn.978-3-85448-042-6_21'
chicago: Alamdari, Par Alizadeh, Guy Avni, Thomas A Henzinger, and Anna Lukina.
“Formal Methods with a Touch of Magic.” In Proceedings of the 20th Conference
on Formal Methods in Computer-Aided Design, 138–47. TU Wien Academic Press,
2020. https://doi.org/10.34727/2020/isbn.978-3-85448-042-6_21.
ieee: P. A. Alamdari, G. Avni, T. A. Henzinger, and A. Lukina, “Formal methods with
a touch of magic,” in Proceedings of the 20th Conference on Formal Methods
in Computer-Aided Design, Online Conference, 2020, pp. 138–147.
ista: 'Alamdari PA, Avni G, Henzinger TA, Lukina A. 2020. Formal methods with a
touch of magic. Proceedings of the 20th Conference on Formal Methods in Computer-Aided
Design. FMCAD: Formal Methods in Computer-Aided Design, 138–147.'
mla: Alamdari, Par Alizadeh, et al. “Formal Methods with a Touch of Magic.” Proceedings
of the 20th Conference on Formal Methods in Computer-Aided Design, TU Wien
Academic Press, 2020, pp. 138–47, doi:10.34727/2020/isbn.978-3-85448-042-6_21.
short: P.A. Alamdari, G. Avni, T.A. Henzinger, A. Lukina, in:, Proceedings of the
20th Conference on Formal Methods in Computer-Aided Design, TU Wien Academic Press,
2020, pp. 138–147.
conference:
end_date: 2020-09-24
location: Online Conference
name: ' FMCAD: Formal Methods in Computer-Aided Design'
start_date: 2020-09-21
date_created: 2021-01-24T23:01:10Z
date_published: 2020-09-21T00:00:00Z
date_updated: 2021-02-09T09:39:59Z
day: '21'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.34727/2020/isbn.978-3-85448-042-6_21
file:
- access_level: open_access
checksum: d616d549a0ade78606b16f8a9540820f
content_type: application/pdf
creator: dernst
date_created: 2021-02-09T09:39:02Z
date_updated: 2021-02-09T09:39:02Z
file_id: '9109'
file_name: 2020_FMCAD_Alamdari.pdf
file_size: 990999
relation: main_file
success: 1
file_date_updated: 2021-02-09T09:39:02Z
has_accepted_license: '1'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 138-147
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the 20th Conference on Formal Methods in Computer-Aided
Design
publication_identifier:
eissn:
- 2708-7824
isbn:
- '9783854480426'
publication_status: published
publisher: TU Wien Academic Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Formal methods with a touch of magic
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '9632'
abstract:
- lang: eng
text: "Second-order information, in the form of Hessian- or Inverse-Hessian-vector
products, is a fundamental tool for solving optimization problems. Recently, there
has been significant interest in utilizing this information in the context of
deep\r\nneural networks; however, relatively little is known about the quality
of existing approximations in this context. Our work examines this question, identifies
issues with existing approaches, and proposes a method called WoodFisher to compute
a faithful and efficient estimate of the inverse Hessian. Our main application
is to neural network compression, where we build on the classic Optimal Brain
Damage/Surgeon framework. We demonstrate that WoodFisher significantly outperforms
popular state-of-the-art methods for oneshot pruning. Further, even when iterative,
gradual pruning is allowed, our method results in a gain in test accuracy over
the state-of-the-art approaches, for standard image classification datasets such
as ImageNet ILSVRC. We examine how our method can be extended to take into account
first-order information, as well as\r\nillustrate its ability to automatically
set layer-wise pruning thresholds and perform compression in the limited-data
regime. The code is available at the following link, https://github.com/IST-DASLab/WoodFisher."
acknowledgement: This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML). Also, we would like to thank Alexander Shevchenko,
Alexandra Peste, and other members of the group for fruitful discussions.
article_processing_charge: No
author:
- first_name: Sidak Pal
full_name: Singh, Sidak Pal
id: DD138E24-D89D-11E9-9DC0-DEF6E5697425
last_name: Singh
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Singh SP, Alistarh D-A. WoodFisher: Efficient second-order approximation for
neural network compression. In: Advances in Neural Information Processing Systems.
Vol 33. Curran Associates; 2020:18098-18109.'
apa: 'Singh, S. P., & Alistarh, D.-A. (2020). WoodFisher: Efficient second-order
approximation for neural network compression. In Advances in Neural Information
Processing Systems (Vol. 33, pp. 18098–18109). Vancouver, Canada: Curran Associates.'
chicago: 'Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order
Approximation for Neural Network Compression.” In Advances in Neural Information
Processing Systems, 33:18098–109. Curran Associates, 2020.'
ieee: 'S. P. Singh and D.-A. Alistarh, “WoodFisher: Efficient second-order approximation
for neural network compression,” in Advances in Neural Information Processing
Systems, Vancouver, Canada, 2020, vol. 33, pp. 18098–18109.'
ista: 'Singh SP, Alistarh D-A. 2020. WoodFisher: Efficient second-order approximation
for neural network compression. Advances in Neural Information Processing Systems.
NeurIPS: Conference on Neural Information Processing Systems vol. 33, 18098–18109.'
mla: 'Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order
Approximation for Neural Network Compression.” Advances in Neural Information
Processing Systems, vol. 33, Curran Associates, 2020, pp. 18098–109.'
short: S.P. Singh, D.-A. Alistarh, in:, Advances in Neural Information Processing
Systems, Curran Associates, 2020, pp. 18098–18109.
conference:
end_date: 2020-12-12
location: Vancouver, Canada
name: 'NeurIPS: Conference on Neural Information Processing Systems'
start_date: 2020-12-06
date_created: 2021-07-04T22:01:26Z
date_published: 2020-12-06T00:00:00Z
date_updated: 2023-02-23T14:03:06Z
day: '06'
department:
- _id: DaAl
- _id: ToHe
ec_funded: 1
external_id:
arxiv:
- '2004.14340'
intvolume: ' 33'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2020/hash/d1ff1ec86b62cd5f3903ff19c3a326b2-Abstract.html
month: '12'
oa: 1
oa_version: Published Version
page: 18098-18109
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Advances in Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713829546'
issn:
- '10495258'
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'WoodFisher: Efficient second-order approximation for neural network compression'
type: conference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 33
year: '2020'
...
---
_id: '9103'
abstract:
- lang: eng
text: 'We introduce LRT-NG, a set of techniques and an associated toolset that computes
a reachtube (an over-approximation of the set of reachable states over a given
time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the
state-of-the-art Langrangian Reachability and its associated tool LRT. From a
theoretical perspective, LRT-NG is superior to LRT in three ways. First, it uses
for the first time an analytically computed metric for the propagated ball which
is proven to minimize the ball’s volume. We emphasize that the metric computation
is the centerpiece of all bloating-based techniques. Secondly, it computes the
next reachset as the intersection of two balls: one based on the Cartesian metric
and the other on the new metric. While the two metrics were previously considered
opposing approaches, their joint use considerably tightens the reachtubes. Thirdly,
it avoids the "wrapping effect" associated with the validated integration of the
center of the reachset, by optimally absorbing the interval approximation in the
radius of the next ball. From a tool-development perspective, LRT-NG is superior
to LRT in two ways. First, it is a standalone tool that no longer relies on CAPD.
This required the implementation of the Lohner method and a Runge-Kutta time-propagation
method. Secondly, it has an improved interface, allowing the input model and initial
conditions to be provided as external input files. Our experiments on a comprehensive
set of benchmarks, including two Neural ODEs, demonstrates LRT-NG’s superior performance
compared to LRT, CAPD, and Flow*.'
acknowledgement: "The authors would like to thank Ramin Hasani and Guillaume Berger
for intellectual discussions about the research which lead to the generation of
new ideas. ML was supported in part by the Austrian Science Fund (FWF) under grant
Z211-N23 (Wittgenstein Award). Smolka’s research was supported by NSF grants CPS-1446832
and CCF-1918225. Gruenbacher is funded by FWF project W1255-N23. JC was partially
supported by NAWA Polish Returns grant\r\nPPN/PPO/2018/1/00029.\r\n"
article_processing_charge: No
author:
- first_name: Sophie
full_name: Gruenbacher, Sophie
last_name: Gruenbacher
- first_name: Jacek
full_name: Cyranka, Jacek
last_name: Cyranka
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Md Ariful
full_name: Islam, Md Ariful
last_name: Islam
- first_name: Scott A.
full_name: Smolka, Scott A.
last_name: Smolka
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
citation:
ama: 'Gruenbacher S, Cyranka J, Lechner M, Islam MA, Smolka SA, Grosu R. Lagrangian
reachtubes: The next generation. In: Proceedings of the 59th IEEE Conference
on Decision and Control. Vol 2020. IEEE; 2020:1556-1563. doi:10.1109/CDC42340.2020.9304042'
apa: 'Gruenbacher, S., Cyranka, J., Lechner, M., Islam, M. A., Smolka, S. A., &
Grosu, R. (2020). Lagrangian reachtubes: The next generation. In Proceedings
of the 59th IEEE Conference on Decision and Control (Vol. 2020, pp. 1556–1563).
Jeju Islang, Korea (South): IEEE. https://doi.org/10.1109/CDC42340.2020.9304042'
chicago: 'Gruenbacher, Sophie, Jacek Cyranka, Mathias Lechner, Md Ariful Islam,
Scott A. Smolka, and Radu Grosu. “Lagrangian Reachtubes: The next Generation.”
In Proceedings of the 59th IEEE Conference on Decision and Control, 2020:1556–63.
IEEE, 2020. https://doi.org/10.1109/CDC42340.2020.9304042.'
ieee: 'S. Gruenbacher, J. Cyranka, M. Lechner, M. A. Islam, S. A. Smolka, and R.
Grosu, “Lagrangian reachtubes: The next generation,” in Proceedings of the
59th IEEE Conference on Decision and Control, Jeju Islang, Korea (South),
2020, vol. 2020, pp. 1556–1563.'
ista: 'Gruenbacher S, Cyranka J, Lechner M, Islam MA, Smolka SA, Grosu R. 2020.
Lagrangian reachtubes: The next generation. Proceedings of the 59th IEEE Conference
on Decision and Control. CDC: Conference on Decision and Control vol. 2020, 1556–1563.'
mla: 'Gruenbacher, Sophie, et al. “Lagrangian Reachtubes: The next Generation.”
Proceedings of the 59th IEEE Conference on Decision and Control, vol. 2020,
IEEE, 2020, pp. 1556–63, doi:10.1109/CDC42340.2020.9304042.'
short: S. Gruenbacher, J. Cyranka, M. Lechner, M.A. Islam, S.A. Smolka, R. Grosu,
in:, Proceedings of the 59th IEEE Conference on Decision and Control, IEEE, 2020,
pp. 1556–1563.
conference:
end_date: 2020-12-18
location: Jeju Islang, Korea (South)
name: 'CDC: Conference on Decision and Control'
start_date: 2020-12-14
date_created: 2021-02-07T23:01:14Z
date_published: 2020-12-14T00:00:00Z
date_updated: 2021-02-09T09:20:58Z
day: '14'
department:
- _id: ToHe
doi: 10.1109/CDC42340.2020.9304042
external_id:
arxiv:
- '2012.07458'
intvolume: ' 2020'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2012.07458
month: '12'
oa: 1
oa_version: Preprint
page: 1556-1563
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the 59th IEEE Conference on Decision and Control
publication_identifier:
isbn:
- '9781728174471'
issn:
- '07431546'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Lagrangian reachtubes: The next generation'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2020
year: '2020'
...
---
_id: '10672'
abstract:
- lang: eng
text: The family of feedback alignment (FA) algorithms aims to provide a more biologically
motivated alternative to backpropagation (BP), by substituting the computations
that are unrealistic to be implemented in physical brains. While FA algorithms
have been shown to work well in practice, there is a lack of rigorous theory proofing
their learning capabilities. Here we introduce the first feedback alignment algorithm
with provable learning guarantees. In contrast to existing work, we do not require
any assumption about the size or depth of the network except that it has a single
output neuron, i.e., such as for binary classification tasks. We show that our
FA algorithm can deliver its theoretical promises in practice, surpassing the
learning performance of existing FA methods and matching backpropagation in binary
classification tasks. Finally, we demonstrate the limits of our FA variant when
the number of output neurons grows beyond a certain quantity.
acknowledgement: "This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23\r\n(Wittgenstein Award).\r\n"
article_processing_charge: No
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
citation:
ama: 'Lechner M. Learning representations for binary-classification without backpropagation.
In: 8th International Conference on Learning Representations. ICLR; 2020.'
apa: 'Lechner, M. (2020). Learning representations for binary-classification without
backpropagation. In 8th International Conference on Learning Representations.
Virtual ; Addis Ababa, Ethiopia: ICLR.'
chicago: Lechner, Mathias. “Learning Representations for Binary-Classification without
Backpropagation.” In 8th International Conference on Learning Representations.
ICLR, 2020.
ieee: M. Lechner, “Learning representations for binary-classification without backpropagation,”
in 8th International Conference on Learning Representations, Virtual ;
Addis Ababa, Ethiopia, 2020.
ista: 'Lechner M. 2020. Learning representations for binary-classification without
backpropagation. 8th International Conference on Learning Representations. ICLR:
International Conference on Learning Representations.'
mla: Lechner, Mathias. “Learning Representations for Binary-Classification without
Backpropagation.” 8th International Conference on Learning Representations,
ICLR, 2020.
short: M. Lechner, in:, 8th International Conference on Learning Representations,
ICLR, 2020.
conference:
end_date: 2020-05-01
location: Virtual ; Addis Ababa, Ethiopia
name: 'ICLR: International Conference on Learning Representations'
start_date: 2020-04-26
date_created: 2022-01-25T15:50:00Z
date_published: 2020-03-11T00:00:00Z
date_updated: 2023-04-03T07:33:40Z
day: '11'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
file:
- access_level: open_access
checksum: ea13d42dd4541ddb239b6a75821fd6c9
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:35:17Z
date_updated: 2022-01-26T07:35:17Z
file_id: '10677'
file_name: iclr_2020.pdf
file_size: 249431
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:35:17Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=Bke61krFvS
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 8th International Conference on Learning Representations
publication_status: published
publisher: ICLR
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning representations for binary-classification without backpropagation
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '7808'
abstract:
- lang: eng
text: Quantization converts neural networks into low-bit fixed-point computations
which can be carried out by efficient integer-only hardware, and is standard practice
for the deployment of neural networks on real-time embedded devices. However,
like their real-numbered counterpart, quantized networks are not immune to malicious
misclassification caused by adversarial attacks. We investigate how quantization
affects a network’s robustness to adversarial attacks, which is a formal verification
question. We show that neither robustness nor non-robustness are monotonic with
changing the number of bits for the representation and, also, neither are preserved
by quantization from a real-numbered network. For this reason, we introduce a
verification method for quantized neural networks which, using SMT solving over
bit-vectors, accounts for their exact, bit-precise semantics. We built a tool
and analyzed the effect of quantization on a classifier for the MNIST dataset.
We demonstrate that, compared to our method, existing methods for the analysis
of real-numbered networks often derive false conclusions about their quantizations,
both when determining robustness and when detecting attacks, and that existing
methods for quantized networks often miss attacks. Furthermore, we applied our
method beyond robustness, showing how the number of bits in quantization enlarges
the gender bias of a predictor for students’ grades.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Mirco
full_name: Giacobbe, Mirco
id: 3444EA5E-F248-11E8-B48F-1D18A9856A87
last_name: Giacobbe
orcid: 0000-0001-8180-0904
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
citation:
ama: 'Giacobbe M, Henzinger TA, Lechner M. How many bits does it take to quantize
your neural network? In: International Conference on Tools and Algorithms for
the Construction and Analysis of Systems. Vol 12079. Springer Nature; 2020:79-97.
doi:10.1007/978-3-030-45237-7_5'
apa: 'Giacobbe, M., Henzinger, T. A., & Lechner, M. (2020). How many bits does
it take to quantize your neural network? In International Conference on Tools
and Algorithms for the Construction and Analysis of Systems (Vol. 12079, pp.
79–97). Dublin, Ireland: Springer Nature. https://doi.org/10.1007/978-3-030-45237-7_5'
chicago: Giacobbe, Mirco, Thomas A Henzinger, and Mathias Lechner. “How Many Bits
Does It Take to Quantize Your Neural Network?” In International Conference
on Tools and Algorithms for the Construction and Analysis of Systems, 12079:79–97.
Springer Nature, 2020. https://doi.org/10.1007/978-3-030-45237-7_5.
ieee: M. Giacobbe, T. A. Henzinger, and M. Lechner, “How many bits does it take
to quantize your neural network?,” in International Conference on Tools and
Algorithms for the Construction and Analysis of Systems, Dublin, Ireland,
2020, vol. 12079, pp. 79–97.
ista: 'Giacobbe M, Henzinger TA, Lechner M. 2020. How many bits does it take to
quantize your neural network? International Conference on Tools and Algorithms
for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for
the Construction and Analysis of Systems, LNCS, vol. 12079, 79–97.'
mla: Giacobbe, Mirco, et al. “How Many Bits Does It Take to Quantize Your Neural
Network?” International Conference on Tools and Algorithms for the Construction
and Analysis of Systems, vol. 12079, Springer Nature, 2020, pp. 79–97, doi:10.1007/978-3-030-45237-7_5.
short: M. Giacobbe, T.A. Henzinger, M. Lechner, in:, International Conference on
Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature,
2020, pp. 79–97.
conference:
end_date: 2020-04-30
location: Dublin, Ireland
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2020-04-25
date_created: 2020-05-10T22:00:49Z
date_published: 2020-04-17T00:00:00Z
date_updated: 2023-06-23T07:01:11Z
day: '17'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-030-45237-7_5
file:
- access_level: open_access
checksum: f19905a42891fe5ce93d69143fa3f6fb
content_type: application/pdf
creator: dernst
date_created: 2020-05-26T12:48:15Z
date_updated: 2020-07-14T12:48:03Z
file_id: '7893'
file_name: 2020_TACAS_Giacobbe.pdf
file_size: 2744030
relation: main_file
file_date_updated: 2020-07-14T12:48:03Z
has_accepted_license: '1'
intvolume: ' 12079'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 79-97
project:
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: International Conference on Tools and Algorithms for the Construction
and Analysis of Systems
publication_identifier:
eissn:
- '16113349'
isbn:
- '9783030452360'
issn:
- '03029743'
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: How many bits does it take to quantize your neural network?
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 12079
year: '2020'
...
---
_id: '6761'
abstract:
- lang: eng
text: In resource allocation games, selfish players share resources that are needed
in order to fulfill their objectives. The cost of using a resource depends on
the load on it. In the traditional setting, the players make their choices concurrently
and in one-shot. That is, a strategy for a player is a subset of the resources.
We introduce and study dynamic resource allocation games. In this setting, the
game proceeds in phases. In each phase each player chooses one resource. A scheduler
dictates the order in which the players proceed in a phase, possibly scheduling
several players to proceed concurrently. The game ends when each player has collected
a set of resources that fulfills his objective. The cost for each player then
depends on this set as well as on the load on the resources in it – we consider
both congestion and cost-sharing games. We argue that the dynamic setting is the
suitable setting for many applications in practice. We study the stability of
dynamic resource allocation games, where the appropriate notion of stability is
that of subgame perfect equilibrium, study the inefficiency incurred due to selfish
behavior, and also study problems that are particular to the dynamic setting,
like constraints on the order in which resources can be chosen or the problem
of finding a scheduler that achieves stability.
article_processing_charge: No
article_type: original
author:
- first_name: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000−0002−2985−7724
- first_name: Orna
full_name: Kupferman, Orna
last_name: Kupferman
citation:
ama: Avni G, Henzinger TA, Kupferman O. Dynamic resource allocation games. Theoretical
Computer Science. 2020;807:42-55. doi:10.1016/j.tcs.2019.06.031
apa: Avni, G., Henzinger, T. A., & Kupferman, O. (2020). Dynamic resource allocation
games. Theoretical Computer Science. Elsevier. https://doi.org/10.1016/j.tcs.2019.06.031
chicago: Avni, Guy, Thomas A Henzinger, and Orna Kupferman. “Dynamic Resource Allocation
Games.” Theoretical Computer Science. Elsevier, 2020. https://doi.org/10.1016/j.tcs.2019.06.031.
ieee: G. Avni, T. A. Henzinger, and O. Kupferman, “Dynamic resource allocation games,”
Theoretical Computer Science, vol. 807. Elsevier, pp. 42–55, 2020.
ista: Avni G, Henzinger TA, Kupferman O. 2020. Dynamic resource allocation games.
Theoretical Computer Science. 807, 42–55.
mla: Avni, Guy, et al. “Dynamic Resource Allocation Games.” Theoretical Computer
Science, vol. 807, Elsevier, 2020, pp. 42–55, doi:10.1016/j.tcs.2019.06.031.
short: G. Avni, T.A. Henzinger, O. Kupferman, Theoretical Computer Science 807 (2020)
42–55.
date_created: 2019-08-04T21:59:20Z
date_published: 2020-02-06T00:00:00Z
date_updated: 2023-08-17T13:52:49Z
day: '06'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1016/j.tcs.2019.06.031
external_id:
isi:
- '000512219400004'
file:
- access_level: open_access
checksum: e86635417f45eb2cd75778f91382f737
content_type: application/pdf
creator: dernst
date_created: 2020-10-09T06:31:22Z
date_updated: 2020-10-09T06:31:22Z
file_id: '8639'
file_name: 2020_TheoreticalCS_Avni.pdf
file_size: 1413001
relation: main_file
success: 1
file_date_updated: 2020-10-09T06:31:22Z
has_accepted_license: '1'
intvolume: ' 807'
isi: 1
language:
- iso: eng
month: '02'
oa: 1
oa_version: Submitted Version
page: 42-55
project:
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 264B3912-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02369
name: Formal Methods meets Algorithmic Game Theory
publication: Theoretical Computer Science
publication_identifier:
issn:
- '03043975'
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
record:
- id: '1341'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Dynamic resource allocation games
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 807
year: '2020'
...
---
_id: '7505'
abstract:
- lang: eng
text: Neural networks have demonstrated unmatched performance in a range of classification
tasks. Despite numerous efforts of the research community, novelty detection remains
one of the significant limitations of neural networks. The ability to identify
previously unseen inputs as novel is crucial for our understanding of the decisions
made by neural networks. At runtime, inputs not falling into any of the categories
learned during training cannot be classified correctly by the neural network.
Existing approaches treat the neural network as a black box and try to detect
novel inputs based on the confidence of the output predictions. However, neural
networks are not trained to reduce their confidence for novel inputs, which limits
the effectiveness of these approaches. We propose a framework to monitor a neural
network by observing the hidden layers. We employ a common abstraction from program
analysis - boxes - to identify novel behaviors in the monitored layers, i.e.,
inputs that cause behaviors outside the box. For each neuron, the boxes range
over the values seen in training. The framework is efficient and flexible to achieve
a desired trade-off between raising false warnings and detecting novel inputs.
We illustrate the performance and the robustness to variability in the unknown
classes on popular image-classification benchmarks.
acknowledgement: We thank Christoph Lampert and Nikolaus Mayer for fruitful discussions.
This research was supported in part by the Austrian Science Fund (FWF) under grants
S11402-N23 (RiSE/SHiNE) and Z211-N23 (Wittgenstein Award) and the European Union’s
Horizon 2020 research and innovation programme under the Marie SkłodowskaCurie grant
agreement No. 754411.
alternative_title:
- Frontiers in Artificial Intelligence and Applications
article_processing_charge: No
author:
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Anna
full_name: Lukina, Anna
id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425
last_name: Lukina
- first_name: Christian
full_name: Schilling, Christian
id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87
last_name: Schilling
orcid: 0000-0003-3658-1065
citation:
ama: 'Henzinger TA, Lukina A, Schilling C. Outside the box: Abstraction-based monitoring
of neural networks. In: 24th European Conference on Artificial Intelligence.
Vol 325. IOS Press; 2020:2433-2440. doi:10.3233/FAIA200375'
apa: 'Henzinger, T. A., Lukina, A., & Schilling, C. (2020). Outside the box:
Abstraction-based monitoring of neural networks. In 24th European Conference
on Artificial Intelligence (Vol. 325, pp. 2433–2440). Santiago de Compostela,
Spain: IOS Press. https://doi.org/10.3233/FAIA200375'
chicago: 'Henzinger, Thomas A, Anna Lukina, and Christian Schilling. “Outside the
Box: Abstraction-Based Monitoring of Neural Networks.” In 24th European Conference
on Artificial Intelligence, 325:2433–40. IOS Press, 2020. https://doi.org/10.3233/FAIA200375.'
ieee: 'T. A. Henzinger, A. Lukina, and C. Schilling, “Outside the box: Abstraction-based
monitoring of neural networks,” in 24th European Conference on Artificial Intelligence,
Santiago de Compostela, Spain, 2020, vol. 325, pp. 2433–2440.'
ista: 'Henzinger TA, Lukina A, Schilling C. 2020. Outside the box: Abstraction-based
monitoring of neural networks. 24th European Conference on Artificial Intelligence.
ECAI: European Conference on Artificial Intelligence, Frontiers in Artificial
Intelligence and Applications, vol. 325, 2433–2440.'
mla: 'Henzinger, Thomas A., et al. “Outside the Box: Abstraction-Based Monitoring
of Neural Networks.” 24th European Conference on Artificial Intelligence,
vol. 325, IOS Press, 2020, pp. 2433–40, doi:10.3233/FAIA200375.'
short: T.A. Henzinger, A. Lukina, C. Schilling, in:, 24th European Conference on
Artificial Intelligence, IOS Press, 2020, pp. 2433–2440.
conference:
end_date: 2020-09-08
location: Santiago de Compostela, Spain
name: 'ECAI: European Conference on Artificial Intelligence'
start_date: 2020-08-29
date_created: 2020-02-21T16:44:03Z
date_published: 2020-02-24T00:00:00Z
date_updated: 2023-08-18T06:38:16Z
day: '24'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.3233/FAIA200375
ec_funded: 1
external_id:
arxiv:
- '1911.09032'
isi:
- '000650971303002'
file:
- access_level: open_access
checksum: 80642fa0b6cd7da95dcd87d63789ad5e
content_type: application/pdf
creator: dernst
date_created: 2020-09-21T07:12:32Z
date_updated: 2020-09-21T07:12:32Z
file_id: '8540'
file_name: 2020_ECAI_Henzinger.pdf
file_size: 1692214
relation: main_file
success: 1
file_date_updated: 2020-09-21T07:12:32Z
has_accepted_license: '1'
intvolume: ' 325'
isi: 1
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 2433-2440
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 24th European Conference on Artificial Intelligence
publication_status: published
publisher: IOS Press
quality_controlled: '1'
status: public
title: 'Outside the box: Abstraction-based monitoring of neural networks'
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 325
year: '2020'
...