--- _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: - iso: eng 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' ...