---
_id: '6354'
abstract:
- lang: eng
text: Blood platelets are critical for hemostasis and thrombosis, but also play
diverse roles during immune responses. We have recently reported that platelets
migrate at sites of infection in vitro and in vivo. Importantly, platelets use
their ability to migrate to collect and bundle fibrin (ogen)-bound bacteria accomplishing
efficient intravascular bacterial trapping. Here, we describe a method that allows
analyzing platelet migration in vitro, focusing on their ability to collect bacteria
and trap bacteria under flow.
acknowledgement: ' FöFoLe project 947 (F.G.), the Friedrich-Baur-Stiftung project
41/16 (F.G.)'
article_number: e3018
author:
- first_name: Shuxia
full_name: Fan, Shuxia
last_name: Fan
- first_name: Michael
full_name: Lorenz, Michael
last_name: Lorenz
- first_name: Steffen
full_name: Massberg, Steffen
last_name: Massberg
- first_name: Florian R
full_name: Gärtner, Florian R
id: 397A88EE-F248-11E8-B48F-1D18A9856A87
last_name: Gärtner
orcid: 0000-0001-6120-3723
citation:
ama: Fan S, Lorenz M, Massberg S, Gärtner FR. Platelet migration and bacterial trapping
assay under flow. Bio-Protocol. 2018;8(18). doi:10.21769/bioprotoc.3018
apa: Fan, S., Lorenz, M., Massberg, S., & Gärtner, F. R. (2018). Platelet migration
and bacterial trapping assay under flow. Bio-Protocol. Bio-Protocol. https://doi.org/10.21769/bioprotoc.3018
chicago: Fan, Shuxia, Michael Lorenz, Steffen Massberg, and Florian R Gärtner. “Platelet
Migration and Bacterial Trapping Assay under Flow.” Bio-Protocol. Bio-Protocol,
2018. https://doi.org/10.21769/bioprotoc.3018.
ieee: S. Fan, M. Lorenz, S. Massberg, and F. R. Gärtner, “Platelet migration and
bacterial trapping assay under flow,” Bio-Protocol, vol. 8, no. 18. Bio-Protocol,
2018.
ista: Fan S, Lorenz M, Massberg S, Gärtner FR. 2018. Platelet migration and bacterial
trapping assay under flow. Bio-Protocol. 8(18), e3018.
mla: Fan, Shuxia, et al. “Platelet Migration and Bacterial Trapping Assay under
Flow.” Bio-Protocol, vol. 8, no. 18, e3018, Bio-Protocol, 2018, doi:10.21769/bioprotoc.3018.
short: S. Fan, M. Lorenz, S. Massberg, F.R. Gärtner, Bio-Protocol 8 (2018).
date_created: 2019-04-29T09:40:33Z
date_published: 2018-09-20T00:00:00Z
date_updated: 2021-01-12T08:07:12Z
day: '20'
ddc:
- '570'
department:
- _id: MiSi
doi: 10.21769/bioprotoc.3018
ec_funded: 1
file:
- access_level: open_access
checksum: d4588377e789da7f360b553ae02c5119
content_type: application/pdf
creator: dernst
date_created: 2019-04-30T08:04:33Z
date_updated: 2020-07-14T12:47:28Z
file_id: '6360'
file_name: 2018_BioProtocol_Fan.pdf
file_size: 2928337
relation: main_file
file_date_updated: 2020-07-14T12:47:28Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '18'
keyword:
- Platelets
- Cell migration
- Bacteria
- Shear flow
- Fibrinogen
- E. coli
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 260AA4E2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '747687'
name: Mechanical Adaptation of Lamellipodial Actin Networks in Migrating Cells
publication: Bio-Protocol
publication_identifier:
issn:
- 2331-8325
publication_status: published
publisher: Bio-Protocol
quality_controlled: '1'
status: public
title: Platelet migration and bacterial trapping assay under flow
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: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2018'
...
---
_id: '6459'
author:
- first_name: Barbara
full_name: Petritsch, Barbara
id: 406048EC-F248-11E8-B48F-1D18A9856A87
last_name: Petritsch
orcid: 0000-0003-2724-4614
citation:
ama: Petritsch B. Open Access at IST Austria 2009-2017. IST Austria; 2018.
doi:10.5281/zenodo.1410279
apa: 'Petritsch, B. (2018). Open Access at IST Austria 2009-2017. Presented
at the Open-Access-Tage, Graz, Austria: IST Austria. https://doi.org/10.5281/zenodo.1410279'
chicago: Petritsch, Barbara. Open Access at IST Austria 2009-2017. IST Austria,
2018. https://doi.org/10.5281/zenodo.1410279.
ieee: B. Petritsch, Open Access at IST Austria 2009-2017. IST Austria, 2018.
ista: Petritsch B. 2018. Open Access at IST Austria 2009-2017, IST Austria,p.
mla: Petritsch, Barbara. Open Access at IST Austria 2009-2017. IST Austria,
2018, doi:10.5281/zenodo.1410279.
short: B. Petritsch, Open Access at IST Austria 2009-2017, IST Austria, 2018.
conference:
end_date: 2018-09-26
location: Graz, Austria
name: Open-Access-Tage
start_date: 2018-09-24
date_created: 2019-05-16T07:27:14Z
date_published: 2018-09-24T00:00:00Z
date_updated: 2020-07-14T23:06:21Z
day: '24'
ddc:
- '020'
department:
- _id: E-Lib
doi: 10.5281/zenodo.1410279
file:
- access_level: open_access
checksum: 9063ab4d10ea93353c3a03bbf53fbcf1
content_type: application/pdf
creator: dernst
date_created: 2019-05-16T07:26:25Z
date_updated: 2020-07-14T12:47:30Z
file_id: '6460'
file_name: Poster_Beitrag_125_Petritsch.pdf
file_size: 1967778
relation: main_file
file_date_updated: 2020-07-14T12:47:30Z
has_accepted_license: '1'
keyword:
- Open Access
- Publication Analysis
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication_status: published
publisher: IST Austria
status: public
title: Open Access at IST Austria 2009-2017
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_poster
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '690'
abstract:
- lang: eng
text: We consider spectral properties and the edge universality of sparse random
matrices, the class of random matrices that includes the adjacency matrices of
the Erdős–Rényi graph model G(N, p). We prove a local law for the eigenvalue density
up to the spectral edges. Under a suitable condition on the sparsity, we also
prove that the rescaled extremal eigenvalues exhibit GOE Tracy–Widom fluctuations
if a deterministic shift of the spectral edge due to the sparsity is included.
For the adjacency matrix of the Erdős–Rényi graph this establishes the Tracy–Widom
fluctuations of the second largest eigenvalue when p is much larger than N−2/3
with a deterministic shift of order (Np)−1.
article_number: 543-616
author:
- first_name: Jii
full_name: Lee, Jii
last_name: Lee
- first_name: Kevin
full_name: Schnelli, Kevin
id: 434AD0AE-F248-11E8-B48F-1D18A9856A87
last_name: Schnelli
orcid: 0000-0003-0954-3231
citation:
ama: Lee J, Schnelli K. Local law and Tracy–Widom limit for sparse random matrices.
Probability Theory and Related Fields. 2018;171(1-2). doi:10.1007/s00440-017-0787-8
apa: Lee, J., & Schnelli, K. (2018). Local law and Tracy–Widom limit for sparse
random matrices. Probability Theory and Related Fields. Springer. https://doi.org/10.1007/s00440-017-0787-8
chicago: Lee, Jii, and Kevin Schnelli. “Local Law and Tracy–Widom Limit for Sparse
Random Matrices.” Probability Theory and Related Fields. Springer, 2018.
https://doi.org/10.1007/s00440-017-0787-8.
ieee: J. Lee and K. Schnelli, “Local law and Tracy–Widom limit for sparse random
matrices,” Probability Theory and Related Fields, vol. 171, no. 1–2. Springer,
2018.
ista: Lee J, Schnelli K. 2018. Local law and Tracy–Widom limit for sparse random
matrices. Probability Theory and Related Fields. 171(1–2), 543–616.
mla: Lee, Jii, and Kevin Schnelli. “Local Law and Tracy–Widom Limit for Sparse Random
Matrices.” Probability Theory and Related Fields, vol. 171, no. 1–2, 543–616,
Springer, 2018, doi:10.1007/s00440-017-0787-8.
short: J. Lee, K. Schnelli, Probability Theory and Related Fields 171 (2018).
date_created: 2018-12-11T11:47:56Z
date_published: 2018-06-14T00:00:00Z
date_updated: 2021-01-12T08:09:33Z
day: '14'
department:
- _id: LaEr
doi: 10.1007/s00440-017-0787-8
ec_funded: 1
external_id:
arxiv:
- '1605.08767'
intvolume: ' 171'
issue: 1-2
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1605.08767
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 258DCDE6-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '338804'
name: Random matrices, universality and disordered quantum systems
publication: Probability Theory and Related Fields
publication_status: published
publisher: Springer
publist_id: '7017'
quality_controlled: '1'
scopus_import: 1
status: public
title: Local law and Tracy–Widom limit for sparse random matrices
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 171
year: '2018'
...
---
_id: '703'
abstract:
- lang: eng
text: We consider the NP-hard problem of MAP-inference for undirected discrete graphical
models. We propose a polynomial time and practically efficient algorithm for finding
a part of its optimal solution. Specifically, our algorithm marks some labels
of the considered graphical model either as (i) optimal, meaning that they belong
to all optimal solutions of the inference problem; (ii) non-optimal if they provably
do not belong to any solution. With access to an exact solver of a linear programming
relaxation to the MAP-inference problem, our algorithm marks the maximal possible
(in a specified sense) number of labels. We also present a version of the algorithm,
which has access to a suboptimal dual solver only and still can ensure the (non-)optimality
for the marked labels, although the overall number of the marked labels may decrease.
We propose an efficient implementation, which runs in time comparable to a single
run of a suboptimal dual solver. Our method is well-scalable and shows state-of-the-art
results on computational benchmarks from machine learning and computer vision.
author:
- first_name: Alexander
full_name: Shekhovtsov, Alexander
last_name: Shekhovtsov
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Bogdan
full_name: Savchynskyy, Bogdan
last_name: Savchynskyy
citation:
ama: Shekhovtsov A, Swoboda P, Savchynskyy B. Maximum persistency via iterative
relaxed inference with graphical models. IEEE Transactions on Pattern Analysis
and Machine Intelligence. 2018;40(7):1668-1682. doi:10.1109/TPAMI.2017.2730884
apa: Shekhovtsov, A., Swoboda, P., & Savchynskyy, B. (2018). Maximum persistency
via iterative relaxed inference with graphical models. IEEE Transactions on
Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2017.2730884
chicago: Shekhovtsov, Alexander, Paul Swoboda, and Bogdan Savchynskyy. “Maximum
Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions
on Pattern Analysis and Machine Intelligence. IEEE, 2018. https://doi.org/10.1109/TPAMI.2017.2730884.
ieee: A. Shekhovtsov, P. Swoboda, and B. Savchynskyy, “Maximum persistency via iterative
relaxed inference with graphical models,” IEEE Transactions on Pattern Analysis
and Machine Intelligence, vol. 40, no. 7. IEEE, pp. 1668–1682, 2018.
ista: Shekhovtsov A, Swoboda P, Savchynskyy B. 2018. Maximum persistency via iterative
relaxed inference with graphical models. IEEE Transactions on Pattern Analysis
and Machine Intelligence. 40(7), 1668–1682.
mla: Shekhovtsov, Alexander, et al. “Maximum Persistency via Iterative Relaxed Inference
with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 40, no. 7, IEEE, 2018, pp. 1668–82, doi:10.1109/TPAMI.2017.2730884.
short: A. Shekhovtsov, P. Swoboda, B. Savchynskyy, IEEE Transactions on Pattern
Analysis and Machine Intelligence 40 (2018) 1668–1682.
date_created: 2018-12-11T11:48:01Z
date_published: 2018-07-01T00:00:00Z
date_updated: 2021-01-12T08:11:32Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/TPAMI.2017.2730884
external_id:
arxiv:
- '1508.07902'
intvolume: ' 40'
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1508.07902
month: '07'
oa: 1
oa_version: Preprint
page: 1668-1682
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_identifier:
issn:
- '01628828'
publication_status: published
publisher: IEEE
publist_id: '6992'
quality_controlled: '1'
scopus_import: 1
status: public
title: Maximum persistency via iterative relaxed inference with graphical models
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 40
year: '2018'
...
---
_id: '7116'
abstract:
- lang: eng
text: 'Training deep learning models has received tremendous research interest recently.
In particular, there has been intensive research on reducing the communication
cost of training when using multiple computational devices, through reducing the
precision of the underlying data representation. Naturally, such methods induce
system trade-offs—lowering communication precision could de-crease communication
overheads and improve scalability; but, on the other hand, it can also reduce
the accuracy of training. In this paper, we study this trade-off space, and ask:Can
low-precision communication consistently improve the end-to-end performance of
training modern neural networks, with no accuracy loss?From the performance point
of view, the answer to this question may appear deceptively easy: compressing
communication through low precision should help when the ratio between communication
and computation is high. However, this answer is less straightforward when we
try to generalize this principle across various neural network architectures (e.g.,
AlexNet vs. ResNet),number of GPUs (e.g., 2 vs. 8 GPUs), machine configurations(e.g.,
EC2 instances vs. NVIDIA DGX-1), communication primitives (e.g., MPI vs. NCCL),
and even different GPU architectures(e.g., Kepler vs. Pascal). Currently, it is
not clear how a realistic realization of all these factors maps to the speed up
provided by low-precision communication. In this paper, we conduct an empirical
study to answer this question and report the insights.'
article_processing_charge: No
author:
- first_name: Demjan
full_name: Grubic, Demjan
last_name: Grubic
- first_name: Leo
full_name: Tam, Leo
last_name: Tam
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Ce
full_name: Zhang, Ce
last_name: Zhang
citation:
ama: 'Grubic D, Tam L, Alistarh D-A, Zhang C. Synchronous multi-GPU training for
deep learning with low-precision communications: An empirical study. In: Proceedings
of the 21st International Conference on Extending Database Technology. OpenProceedings;
2018:145-156. doi:10.5441/002/EDBT.2018.14'
apa: 'Grubic, D., Tam, L., Alistarh, D.-A., & Zhang, C. (2018). Synchronous
multi-GPU training for deep learning with low-precision communications: An empirical
study. In Proceedings of the 21st International Conference on Extending Database
Technology (pp. 145–156). Vienna, Austria: OpenProceedings. https://doi.org/10.5441/002/EDBT.2018.14'
chicago: 'Grubic, Demjan, Leo Tam, Dan-Adrian Alistarh, and Ce Zhang. “Synchronous
Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical
Study.” In Proceedings of the 21st International Conference on Extending Database
Technology, 145–56. OpenProceedings, 2018. https://doi.org/10.5441/002/EDBT.2018.14.'
ieee: 'D. Grubic, L. Tam, D.-A. Alistarh, and C. Zhang, “Synchronous multi-GPU training
for deep learning with low-precision communications: An empirical study,” in Proceedings
of the 21st International Conference on Extending Database Technology, Vienna,
Austria, 2018, pp. 145–156.'
ista: 'Grubic D, Tam L, Alistarh D-A, Zhang C. 2018. Synchronous multi-GPU training
for deep learning with low-precision communications: An empirical study. Proceedings
of the 21st International Conference on Extending Database Technology. EDBT: Conference
on Extending Database Technology, 145–156.'
mla: 'Grubic, Demjan, et al. “Synchronous Multi-GPU Training for Deep Learning with
Low-Precision Communications: An Empirical Study.” Proceedings of the 21st
International Conference on Extending Database Technology, OpenProceedings,
2018, pp. 145–56, doi:10.5441/002/EDBT.2018.14.'
short: D. Grubic, L. Tam, D.-A. Alistarh, C. Zhang, in:, Proceedings of the 21st
International Conference on Extending Database Technology, OpenProceedings, 2018,
pp. 145–156.
conference:
end_date: 2018-03-29
location: Vienna, Austria
name: 'EDBT: Conference on Extending Database Technology'
start_date: 2018-03-26
date_created: 2019-11-26T14:19:11Z
date_published: 2018-03-26T00:00:00Z
date_updated: 2023-02-23T12:59:17Z
day: '26'
ddc:
- '000'
department:
- _id: DaAl
doi: 10.5441/002/EDBT.2018.14
file:
- access_level: open_access
checksum: ec979b56abc71016d6e6adfdadbb4afe
content_type: application/pdf
creator: dernst
date_created: 2019-11-26T14:23:04Z
date_updated: 2020-07-14T12:47:49Z
file_id: '7118'
file_name: 2018_OpenProceedings_Grubic.pdf
file_size: 1603204
relation: main_file
file_date_updated: 2020-07-14T12:47:49Z
has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '03'
oa: 1
oa_version: Published Version
page: 145-156
publication: Proceedings of the 21st International Conference on Extending Database
Technology
publication_identifier:
isbn:
- '9783893180783'
issn:
- 2367-2005
publication_status: published
publisher: OpenProceedings
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Synchronous multi-GPU training for deep learning with low-precision communications:
An empirical study'
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '7407'
abstract:
- lang: eng
text: 'Proofs of space (PoS) [Dziembowski et al., CRYPTO''15] are proof systems
where a prover can convince a verifier that he "wastes" disk space. PoS were introduced
as a more ecological and economical replacement for proofs of work which are currently
used to secure blockchains like Bitcoin. In this work we investigate extensions
of PoS which allow the prover to embed useful data into the dedicated space, which
later can be recovered. Our first contribution is a security proof for the original
PoS from CRYPTO''15 in the random oracle model (the original proof only applied
to a restricted class of adversaries which can store a subset of the data an honest
prover would store). When this PoS is instantiated with recent constructions of
maximally depth robust graphs, our proof implies basically optimal security. As
a second contribution we show three different extensions of this PoS where useful
data can be embedded into the space required by the prover. Our security proof
for the PoS extends (non-trivially) to these constructions. We discuss how some
of these variants can be used as proofs of catalytic space (PoCS), a notion we
put forward in this work, and which basically is a PoS where most of the space
required by the prover can be used to backup useful data. Finally we discuss how
one of the extensions is a candidate construction for a proof of replication (PoR),
a proof system recently suggested in the Filecoin whitepaper. '
alternative_title:
- LIPIcs
article_processing_charge: No
author:
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
citation:
ama: 'Pietrzak KZ. Proofs of catalytic space. In: 10th Innovations in Theoretical
Computer Science Conference (ITCS 2019). Vol 124. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2018:59:1-59:25. doi:10.4230/LIPICS.ITCS.2019.59'
apa: 'Pietrzak, K. Z. (2018). Proofs of catalytic space. In 10th Innovations
in Theoretical Computer Science Conference (ITCS 2019) (Vol. 124, p. 59:1-59:25).
San Diego, CA, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.
https://doi.org/10.4230/LIPICS.ITCS.2019.59'
chicago: Pietrzak, Krzysztof Z. “Proofs of Catalytic Space.” In 10th Innovations
in Theoretical Computer Science Conference (ITCS 2019), 124:59:1-59:25. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2018. https://doi.org/10.4230/LIPICS.ITCS.2019.59.
ieee: K. Z. Pietrzak, “Proofs of catalytic space,” in 10th Innovations in Theoretical
Computer Science Conference (ITCS 2019), San Diego, CA, United States, 2018,
vol. 124, p. 59:1-59:25.
ista: 'Pietrzak KZ. 2018. Proofs of catalytic space. 10th Innovations in Theoretical
Computer Science Conference (ITCS 2019). ITCS: Innovations in theoretical Computer
Science Conference, LIPIcs, vol. 124, 59:1-59:25.'
mla: Pietrzak, Krzysztof Z. “Proofs of Catalytic Space.” 10th Innovations in
Theoretical Computer Science Conference (ITCS 2019), vol. 124, Schloss Dagstuhl
- Leibniz-Zentrum für Informatik, 2018, p. 59:1-59:25, doi:10.4230/LIPICS.ITCS.2019.59.
short: K.Z. Pietrzak, in:, 10th Innovations in Theoretical Computer Science Conference
(ITCS 2019), Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018, p. 59:1-59:25.
conference:
end_date: 2019-01-12
location: San Diego, CA, United States
name: 'ITCS: Innovations in theoretical Computer Science Conference'
start_date: 2019-01-10
date_created: 2020-01-30T09:16:05Z
date_published: 2018-12-31T00:00:00Z
date_updated: 2021-01-12T08:13:26Z
day: '31'
ddc:
- '000'
department:
- _id: KrPi
doi: 10.4230/LIPICS.ITCS.2019.59
ec_funded: 1
file:
- access_level: open_access
checksum: 5cebb7f7849a3beda898f697d755dd96
content_type: application/pdf
creator: dernst
date_created: 2020-02-04T08:17:52Z
date_updated: 2020-07-14T12:47:57Z
file_id: '7443'
file_name: 2018_LIPIcs_Pietrzak.pdf
file_size: 822884
relation: main_file
file_date_updated: 2020-07-14T12:47:57Z
has_accepted_license: '1'
intvolume: ' 124'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2018/194
month: '12'
oa: 1
oa_version: Published Version
page: 59:1-59:25
project:
- _id: 258AA5B2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '682815'
name: Teaching Old Crypto New Tricks
publication: 10th Innovations in Theoretical Computer Science Conference (ITCS 2019)
publication_identifier:
isbn:
- 978-3-95977-095-8
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: 1
status: public
title: Proofs of catalytic space
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: 124
year: '2018'
...
---
_id: '7812'
abstract:
- lang: eng
text: Deep neural networks (DNNs) continue to make significant advances, solving
tasks from image classification to translation or reinforcement learning. One
aspect of the field receiving considerable attention is efficiently executing
deep models in resource-constrained environments, such as mobile or embedded devices.
This paper focuses on this problem, and proposes two new compression methods,
which jointly leverage weight quantization and distillation of larger teacher
networks into smaller student networks. The first method we propose is called
quantized distillation and leverages distillation during the training process,
by incorporating distillation loss, expressed with respect to the teacher, into
the training of a student network whose weights are quantized to a limited set
of levels. The second method, differentiable quantization, optimizes the location
of quantization points through stochastic gradient descent, to better fit the
behavior of the teacher model. We validate both methods through experiments on
convolutional and recurrent architectures. We show that quantized shallow students
can reach similar accuracy levels to full-precision teacher models, while providing
order of magnitude compression, and inference speedup that is linear in the depth
reduction. In sum, our results enable DNNs for resource-constrained environments
to leverage architecture and accuracy advances developed on more powerful devices.
article_processing_charge: No
author:
- first_name: Antonio
full_name: Polino, Antonio
last_name: Polino
- first_name: Razvan
full_name: Pascanu, Razvan
last_name: Pascanu
- 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: 'Polino A, Pascanu R, Alistarh D-A. Model compression via distillation and
quantization. In: 6th International Conference on Learning Representations.
; 2018.'
apa: Polino, A., Pascanu, R., & Alistarh, D.-A. (2018). Model compression via
distillation and quantization. In 6th International Conference on Learning
Representations. Vancouver, Canada.
chicago: Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “Model Compression
via Distillation and Quantization.” In 6th International Conference on Learning
Representations, 2018.
ieee: A. Polino, R. Pascanu, and D.-A. Alistarh, “Model compression via distillation
and quantization,” in 6th International Conference on Learning Representations,
Vancouver, Canada, 2018.
ista: 'Polino A, Pascanu R, Alistarh D-A. 2018. Model compression via distillation
and quantization. 6th International Conference on Learning Representations. ICLR:
International Conference on Learning Representations.'
mla: Polino, Antonio, et al. “Model Compression via Distillation and Quantization.”
6th International Conference on Learning Representations, 2018.
short: A. Polino, R. Pascanu, D.-A. Alistarh, in:, 6th International Conference
on Learning Representations, 2018.
conference:
end_date: 2018-05-03
location: Vancouver, Canada
name: 'ICLR: International Conference on Learning Representations'
start_date: 2018-04-30
date_created: 2020-05-10T22:00:51Z
date_published: 2018-05-01T00:00:00Z
date_updated: 2023-02-23T13:18:41Z
day: '01'
ddc:
- '000'
department:
- _id: DaAl
external_id:
arxiv:
- '1802.05668'
file:
- access_level: open_access
checksum: a4336c167978e81891970e4e4517a8c3
content_type: application/pdf
creator: dernst
date_created: 2020-05-26T13:02:00Z
date_updated: 2020-07-14T12:48:03Z
file_id: '7894'
file_name: 2018_ICLR_Polino.pdf
file_size: 308339
relation: main_file
file_date_updated: 2020-07-14T12:48:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
publication: 6th International Conference on Learning Representations
publication_status: published
quality_controlled: '1'
scopus_import: 1
status: public
title: Model compression via distillation and quantization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '8547'
abstract:
- lang: eng
text: The cerebral cortex contains multiple hierarchically organized areas with
distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying
the emergence of this diversity remain unclear. Here, we have quantitatively investigated
the neuronal output of individual progenitor cells in the ventricular zone of
the developing mouse neocortex using a combination of methods that together circumvent
the biases and limitations of individual approaches. We found that individual
cortical progenitor cells show a high degree of stochasticity and generate pyramidal
cell lineages that adopt a wide range of laminar configurations. Mathematical
modelling these lineage data suggests that a small number of progenitor cell populations,
each generating pyramidal cells following different stochastic developmental programs,
suffice to generate the heterogenous complement of pyramidal cell lineages that
collectively build the complex cytoarchitecture of the neocortex.
acknowledgement: We thank I. Andrew and S.E. Bae for excellent technical assistance,
F. Gage for plasmids, and K. Nave (Nex-Cre) for mouse colonies. We thank members
of the Marín and Rico laboratories for stimulating discussions and ideas. Our research
on this topic is supported by grants from the European Research Council (ERC-2017-AdG
787355 to O.M and ERC2016-CoG 725780 to S.H.) and Wellcome Trust (103714MA) to O.M.
L.L. was the recipient of an EMBO long-term postdoctoral fellowship, R.B. received
support from FWF Lise-Meitner program (M 2416) and F.K.W. was supported by an EMBO
postdoctoral fellowship and is currently a Marie Skłodowska-Curie Fellow from the
European Commission under the H2020 Programme.
article_processing_charge: No
author:
- first_name: Alfredo
full_name: Llorca, Alfredo
last_name: Llorca
- first_name: Gabriele
full_name: Ciceri, Gabriele
last_name: Ciceri
- first_name: Robert J
full_name: Beattie, Robert J
id: 2E26DF60-F248-11E8-B48F-1D18A9856A87
last_name: Beattie
orcid: 0000-0002-8483-8753
- first_name: Fong K.
full_name: Wong, Fong K.
last_name: Wong
- first_name: Giovanni
full_name: Diana, Giovanni
last_name: Diana
- first_name: Eleni
full_name: Serafeimidou, Eleni
last_name: Serafeimidou
- first_name: Marian
full_name: Fernández-Otero, Marian
last_name: Fernández-Otero
- first_name: Carmen
full_name: Streicher, Carmen
id: 36BCB99C-F248-11E8-B48F-1D18A9856A87
last_name: Streicher
- first_name: Sebastian J.
full_name: Arnold, Sebastian J.
last_name: Arnold
- first_name: Martin
full_name: Meyer, Martin
last_name: Meyer
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
- first_name: Miguel
full_name: Maravall, Miguel
last_name: Maravall
- first_name: Oscar
full_name: Marín, Oscar
last_name: Marín
citation:
ama: Llorca A, Ciceri G, Beattie RJ, et al. Heterogeneous progenitor cell behaviors
underlie the assembly of neocortical cytoarchitecture. bioRxiv. doi:10.1101/494088
apa: Llorca, A., Ciceri, G., Beattie, R. J., Wong, F. K., Diana, G., Serafeimidou,
E., … Marín, O. (n.d.). Heterogeneous progenitor cell behaviors underlie the assembly
of neocortical cytoarchitecture. bioRxiv. Cold Spring Harbor Laboratory.
https://doi.org/10.1101/494088
chicago: Llorca, Alfredo, Gabriele Ciceri, Robert J Beattie, Fong K. Wong, Giovanni
Diana, Eleni Serafeimidou, Marian Fernández-Otero, et al. “Heterogeneous Progenitor
Cell Behaviors Underlie the Assembly of Neocortical Cytoarchitecture.” BioRxiv.
Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/494088.
ieee: A. Llorca et al., “Heterogeneous progenitor cell behaviors underlie
the assembly of neocortical cytoarchitecture,” bioRxiv. Cold Spring Harbor
Laboratory.
ista: Llorca A, Ciceri G, Beattie RJ, Wong FK, Diana G, Serafeimidou E, Fernández-Otero
M, Streicher C, Arnold SJ, Meyer M, Hippenmeyer S, Maravall M, Marín O. Heterogeneous
progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture.
bioRxiv, 10.1101/494088.
mla: Llorca, Alfredo, et al. “Heterogeneous Progenitor Cell Behaviors Underlie the
Assembly of Neocortical Cytoarchitecture.” BioRxiv, Cold Spring Harbor
Laboratory, doi:10.1101/494088.
short: A. Llorca, G. Ciceri, R.J. Beattie, F.K. Wong, G. Diana, E. Serafeimidou,
M. Fernández-Otero, C. Streicher, S.J. Arnold, M. Meyer, S. Hippenmeyer, M. Maravall,
O. Marín, BioRxiv (n.d.).
date_created: 2020-09-21T12:01:50Z
date_published: 2018-12-13T00:00:00Z
date_updated: 2021-01-12T08:20:00Z
day: '13'
department:
- _id: SiHi
doi: 10.1101/494088
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/494088
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 260018B0-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '725780'
name: Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development
- _id: 264E56E2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02416
name: Molecular Mechanisms Regulating Gliogenesis in the Cerebral Cortex
publication: bioRxiv
publication_status: submitted
publisher: Cold Spring Harbor Laboratory
status: public
title: Heterogeneous progenitor cell behaviors underlie the assembly of neocortical
cytoarchitecture
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '86'
abstract:
- lang: eng
text: Responsiveness—the requirement that every request to a system be eventually
handled—is one of the fundamental liveness properties of a reactive system. Average
response time is a quantitative measure for the responsiveness requirement used
commonly in performance evaluation. We show how average response time can be computed
on state-transition graphs, on Markov chains, and on game graphs. In all three
cases, we give polynomial-time algorithms.
acknowledgement: 'This research was supported in part by the Austrian Science Fund
(FWF) under grants S11402-N23, S11407-N23 (RiSE/SHiNE) and Z211-N23 (Wittgenstein
Award), ERC Start grant (279307: Graph Games), Vienna Science and Technology Fund
(WWTF) through project ICT15-003 and by the National Science Centre (NCN), Poland
under grant 2014/15/D/ST6/04543.'
alternative_title:
- LNCS
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. Computing average response time. In: Lohstroh
M, Derler P, Sirjani M, eds. Principles of Modeling. Vol 10760. Springer;
2018:143-161. doi:10.1007/978-3-319-95246-8_9'
apa: Chatterjee, K., Henzinger, T. A., & Otop, J. (2018). Computing average
response time. In M. Lohstroh, P. Derler, & M. Sirjani (Eds.), Principles
of Modeling (Vol. 10760, pp. 143–161). Springer. https://doi.org/10.1007/978-3-319-95246-8_9
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, and Jan Otop. “Computing Average
Response Time.” In Principles of Modeling, edited by Marten Lohstroh, Patricia
Derler, and Marjan Sirjani, 10760:143–61. Springer, 2018. https://doi.org/10.1007/978-3-319-95246-8_9.
ieee: K. Chatterjee, T. A. Henzinger, and J. Otop, “Computing average response time,”
in Principles of Modeling, vol. 10760, M. Lohstroh, P. Derler, and M. Sirjani,
Eds. Springer, 2018, pp. 143–161.
ista: 'Chatterjee K, Henzinger TA, Otop J. 2018.Computing average response time.
In: Principles of Modeling. LNCS, vol. 10760, 143–161.'
mla: Chatterjee, Krishnendu, et al. “Computing Average Response Time.” Principles
of Modeling, edited by Marten Lohstroh et al., vol. 10760, Springer, 2018,
pp. 143–61, doi:10.1007/978-3-319-95246-8_9.
short: K. Chatterjee, T.A. Henzinger, J. Otop, in:, M. Lohstroh, P. Derler, M. Sirjani
(Eds.), Principles of Modeling, Springer, 2018, pp. 143–161.
date_created: 2018-12-11T11:44:33Z
date_published: 2018-07-20T00:00:00Z
date_updated: 2021-01-12T08:20:14Z
day: '20'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-319-95246-8_9
ec_funded: 1
editor:
- first_name: Marten
full_name: Lohstroh, Marten
last_name: Lohstroh
- first_name: Patricia
full_name: Derler, Patricia
last_name: Derler
- first_name: Marjan
full_name: Sirjani, Marjan
last_name: Sirjani
file:
- access_level: open_access
checksum: 9995c6ce6957333baf616fc4f20be597
content_type: application/pdf
creator: dernst
date_created: 2019-11-19T08:22:18Z
date_updated: 2020-07-14T12:48:14Z
file_id: '7053'
file_name: 2018_PrinciplesModeling_Chatterjee.pdf
file_size: 516307
relation: main_file
file_date_updated: 2020-07-14T12:48:14Z
has_accepted_license: '1'
intvolume: ' 10760'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
page: 143 - 161
project:
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '279307'
name: 'Quantitative Graph Games: Theory and Applications'
- _id: 25892FC0-B435-11E9-9278-68D0E5697425
grant_number: ICT15-003
name: Efficient Algorithms for Computer Aided Verification
publication: Principles of Modeling
publication_status: published
publisher: Springer
publist_id: '7968'
quality_controlled: '1'
scopus_import: 1
status: public
title: Computing average response time
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 10760
year: '2018'
...
---
_id: '9229'
alternative_title:
- Molecular and cellular neuroscience
article_processing_charge: No
article_type: letter_note
author:
- first_name: Johann G
full_name: Danzl, Johann G
id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
last_name: Danzl
orcid: 0000-0001-8559-3973
citation:
ama: Danzl JG. Diffraction-unlimited optical imaging for synaptic physiology. Opera
Medica et Physiologica. 2018;4(S1):11. doi:10.20388/omp2018.00s1.001
apa: Danzl, J. G. (2018). Diffraction-unlimited optical imaging for synaptic physiology.
Opera Medica et Physiologica. Lobachevsky State University of Nizhny Novgorod.
https://doi.org/10.20388/omp2018.00s1.001
chicago: Danzl, Johann G. “Diffraction-Unlimited Optical Imaging for Synaptic Physiology.”
Opera Medica et Physiologica. Lobachevsky State University of Nizhny Novgorod,
2018. https://doi.org/10.20388/omp2018.00s1.001.
ieee: J. G. Danzl, “Diffraction-unlimited optical imaging for synaptic physiology,”
Opera Medica et Physiologica, vol. 4, no. S1. Lobachevsky State University
of Nizhny Novgorod, p. 11, 2018.
ista: Danzl JG. 2018. Diffraction-unlimited optical imaging for synaptic physiology.
Opera Medica et Physiologica. 4(S1), 11.
mla: Danzl, Johann G. “Diffraction-Unlimited Optical Imaging for Synaptic Physiology.”
Opera Medica et Physiologica, vol. 4, no. S1, Lobachevsky State University
of Nizhny Novgorod, 2018, p. 11, doi:10.20388/omp2018.00s1.001.
short: J.G. Danzl, Opera Medica et Physiologica 4 (2018) 11.
date_created: 2021-03-07T23:01:25Z
date_published: 2018-06-30T00:00:00Z
date_updated: 2021-12-03T07:31:05Z
day: '30'
department:
- _id: JoDa
doi: 10.20388/omp2018.00s1.001
intvolume: ' 4'
issue: S1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://operamedphys.org/content/molecular-and-cellular-neuroscience
month: '06'
oa: 1
oa_version: Published Version
page: '11'
publication: Opera Medica et Physiologica
publication_identifier:
eissn:
- 2500-2295
issn:
- 2500-2287
publication_status: published
publisher: Lobachevsky State University of Nizhny Novgorod
quality_controlled: '1'
scopus_import: '1'
status: public
title: Diffraction-unlimited optical imaging for synaptic physiology
type: journal_article
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 4
year: '2018'
...