{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:07:24Z","timestamp":1758272844694,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,5,4]],"date-time":"2022-05-04T00:00:00Z","timestamp":1651622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF","award":["CMMI-2105631"],"award-info":[{"award-number":["CMMI-2105631"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1836900"],"award-info":[{"award-number":["CNS-1836900"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NASA University Leadership initiative","award":["80NSSC20M0163"],"award-info":[{"award-number":["80NSSC20M0163"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,5,4]]},"DOI":"10.1145\/3501710.3519525","type":"proceedings-article","created":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T14:28:32Z","timestamp":1651156112000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods"],"prefix":"10.1145","author":[{"given":"Adam","family":"Thorpe","sequence":"first","affiliation":[{"name":"University Of New Mexico, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meeko","family":"Oishi","sequence":"additional","affiliation":[{"name":"University of New Mexico, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,5,4]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg\u00a0S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org.  Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg\u00a0S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.29007\/f2vb"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.29007\/mqzc"},{"key":"e_1_3_2_1_4_1","volume-title":"ARCH-COMP18 Category Report: Stochastic Modelling. EPiC Series in Computing 54","author":"Abate Alessandro","year":"2018","unstructured":"Alessandro Abate , HAP Blom , Nathalie Cauchi , Sofie Haesaert , Arnd Hartmanns , Kendra Lesser , Meeko Oishi , Vignesh Sivaramakrishnan , and Sadegh Soudjani . 2018. ARCH-COMP18 Category Report: Stochastic Modelling. EPiC Series in Computing 54 ( 2018 ). Alessandro Abate, HAP Blom, Nathalie Cauchi, Sofie Haesaert, Arnd Hartmanns, Kendra Lesser, Meeko Oishi, Vignesh Sivaramakrishnan, and Sadegh Soudjani. 2018. ARCH-COMP18 Category Report: Stochastic Modelling. EPiC Series in Computing 54 (2018)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2008.03.027"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9947-1950-0051437-7"},{"volume-title":"Stochastic optimal control: the discrete time case","author":"Bertsekas P","key":"e_1_3_2_1_7_1","unstructured":"Dimitri\u00a0 P Bertsekas and Steven\u00a0 E Shreve . 1978. Stochastic optimal control: the discrete time case . Elsevier . Dimitri\u00a0P Bertsekas and Steven\u00a0E Shreve. 1978. Stochastic optimal control: the discrete time case. Elsevier."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/153244302760200704"},{"volume-title":"Convex optimization","author":"Boyd Stephen","key":"e_1_3_2_1_9_1","unstructured":"Stephen Boyd , Stephen\u00a0 P Boyd , and Lieven Vandenberghe . 2004. Convex optimization . Cambridge university press . Stephen Boyd, Stephen\u00a0P Boyd, and Lieven Vandenberghe. 2004. Convex optimization. Cambridge university press."},{"key":"e_1_3_2_1_10_1","unstructured":"Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. Openai gym. arXiv preprint arXiv:1606.01540(2016).  Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. Openai gym. arXiv preprint arXiv:1606.01540(2016)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3302504.3313349"},{"key":"e_1_3_2_1_12_1","unstructured":"Fran\u00e7ois Chollet 2015. Keras. https:\/\/keras.io.  Fran\u00e7ois Chollet 2015. Keras. https:\/\/keras.io."},{"volume-title":"Probability and Stochastics. Vol.\u00a0261","author":"\u00c7\u0131nlar Erhan","key":"e_1_3_2_1_13_1","unstructured":"Erhan \u00c7\u0131nlar . 2011. Probability and Stochastics. Vol.\u00a0261 . Springer Science & Business Media . Erhan \u00c7\u0131nlar. 2011. Probability and Stochastics. Vol.\u00a0261. Springer Science & Business Media."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2013.11.003"},{"volume-title":"A Storm is Coming: A Modern Probabilistic Model Checker","author":"Dehnert Christian","key":"e_1_3_2_1_15_1","unstructured":"Christian Dehnert , Sebastian Junges , Joost-Pieter Katoen , and Matthias Volk . 2017. A Storm is Coming: A Modern Probabilistic Model Checker . In Computer Aided Verification, Rupak Majumdar and Viktor Kun\u010dak (Eds.). Springer International Publishing , Cham , 592\u2013600. Christian Dehnert, Sebastian Junges, Joost-Pieter Katoen, and Matthias Volk. 2017. A Storm is Coming: A Modern Probabilistic Model Checker. In Computer Aided Verification, Rupak Majumdar and Viktor Kun\u010dak (Eds.). Springer International Publishing, Cham, 592\u2013600."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2008.12.019"},{"key":"e_1_3_2_1_17_1","unstructured":"Franck Djeumou and Ufuk Topcu. 2021. Learning to Reach Swim Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information. arXiv preprint arXiv:2106.10533(2021).  Franck Djeumou and Ufuk Topcu. 2021. Learning to Reach Swim Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information. arXiv preprint arXiv:2106.10533(2021)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447928.3457355"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3302504.3313351"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/2789272.2886795"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.29007\/zkf6"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the 29th International Coference on International Conference on Machine Learning. 1803\u20131810","author":"Gr\u00fcnew\u00e4lder Steffen","year":"2012","unstructured":"Steffen Gr\u00fcnew\u00e4lder , Guy Lever , Luca Baldassarre , Sam Patterson , Arthur Gretton , and Massimilano Pontil . 2012 . Conditional mean embeddings as regressors . In Proceedings of the 29th International Coference on International Conference on Machine Learning. 1803\u20131810 . Steffen Gr\u00fcnew\u00e4lder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, and Massimilano Pontil. 2012. Conditional mean embeddings as regressors. In Proceedings of the 29th International Coference on International Conference on Machine Learning. 1803\u20131810."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.5555\/3042573.3042778"},{"volume-title":"The Marabou Framework for Verification and Analysis of Deep Neural Networks","author":"Katz Guy","key":"e_1_3_2_1_24_1","unstructured":"Guy Katz , Derek Huang , Duligur Ibeling , Kyle Julian , Christopher Lazarus , Rachel Lim , Parth Shah , Shantanu Thakoor , Haoze Wu , Aleksandar Zelji\u0107 , David\u00a0 L. Dill , Mykel Kochenderfer , and Clark Barrett . 2019. The Marabou Framework for Verification and Analysis of Deep Neural Networks . In Computer Aided Verification, Isil Dillig and Serdar Tasiran (Eds.). Springer International Publishing , Cham , 443\u2013452. Guy Katz, Derek Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zelji\u0107, David\u00a0L. Dill, Mykel Kochenderfer, and Clark Barrett. 2019. The Marabou Framework for Verification and Analysis of Deep Neural Networks. In Computer Aided Verification, Isil Dillig and Serdar Tasiran (Eds.). Springer International Publishing, Cham, 443\u2013452."},{"key":"e_1_3_2_1_25_1","volume-title":"Sampling-based methods for motion planning with constraints. Annual review of control, robotics, and autonomous systems 1","author":"Kingston Zachary","year":"2018","unstructured":"Zachary Kingston , Mark Moll , and Lydia\u00a0 E Kavraki . 2018. Sampling-based methods for motion planning with constraints. Annual review of control, robotics, and autonomous systems 1 ( 2018 ), 159\u2013185. Zachary Kingston, Mark Moll, and Lydia\u00a0E Kavraki. 2018. Sampling-based methods for motion planning with constraints. Annual review of control, robotics, and autonomous systems 1 (2018), 159\u2013185."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-22110-1_47"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3365365.3383469"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2013.6760626"},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Guy Lebanon and S.\u00a0V.\u00a0N. Vishwanathan (Eds.). Vol.\u00a038","author":"Lever Guy","year":"2015","unstructured":"Guy Lever and Ronnie Stafford . 2015 . Modelling Policies in MDPs in Reproducing Kernel Hilbert Space . In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Guy Lebanon and S.\u00a0V.\u00a0N. Vishwanathan (Eds.). Vol.\u00a038 . PMLR, San Diego, California, USA, 590\u2013598. Guy Lever and Ronnie Stafford. 2015. Modelling Policies in MDPs in Reproducing Kernel Hilbert Space. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Guy Lebanon and S.\u00a0V.\u00a0N. Vishwanathan (Eds.). Vol.\u00a038. PMLR, San Diego, California, USA, 590\u2013598."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2016.XII.046"},{"key":"e_1_3_2_1_31_1","volume-title":"On learning vector-valued functions. Neural computation 17, 1","author":"Micchelli A","year":"2005","unstructured":"Charles\u00a0 A Micchelli and Massimiliano Pontil . 2005. On learning vector-valued functions. Neural computation 17, 1 ( 2005 ), 177\u2013204. Charles\u00a0A Micchelli and Massimiliano Pontil. 2005. On learning vector-valued functions. Neural computation 17, 1 (2005), 177\u2013204."},{"key":"e_1_3_2_1_32_1","volume-title":"A measure-theoretic approach to kernel conditional mean embeddings. Advances in Neural Information Processing Systems 33","author":"Park Junhyung","year":"2020","unstructured":"Junhyung Park and Krikamol Muandet . 2020. A measure-theoretic approach to kernel conditional mean embeddings. Advances in Neural Information Processing Systems 33 ( 2020 ). Junhyung Park and Krikamol Muandet. 2020. A measure-theoretic approach to kernel conditional mean embeddings. Advances in Neural Information Processing Systems 33 (2020)."},{"volume-title":"PyTorch: An Imperative Style","author":"Paszke Adam","key":"e_1_3_2_1_33_1","unstructured":"Adam Paszke , Sam Gross , Francisco Massa , Adam Lerer , James Bradbury , Gregory Chanan , Trevor Killeen , Zeming Lin , Natalia Gimelshein , Luca Antiga , Alban Desmaison , Andreas Kopf , Edward Yang , Zachary DeVito , Martin Raison , Alykhan Tejani , Sasank Chilamkurthy , Benoit Steiner , Lu Fang , Junjie Bai , and Soumith Chintala . 2019. PyTorch: An Imperative Style , High-Performance Deep Learning Library . In Advances in Neural Information Processing Systems 32, H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.). Curran Associates, Inc., 8024\u20138035. Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32, H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.). Curran Associates, Inc., 8024\u20138035."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"e_1_3_2_1_35_1","volume-title":"Advances in Neural Information Processing Systems, J.\u00a0Platt, D.\u00a0Koller, Y.\u00a0Singer, and S.\u00a0Roweis (Eds.). Vol.\u00a020. Curran Associates","author":"Rahimi Ali","year":"2007","unstructured":"Ali Rahimi and Benjamin Recht . 2007. Random Features for Large-Scale Kernel Machines . In Advances in Neural Information Processing Systems, J.\u00a0Platt, D.\u00a0Koller, Y.\u00a0Singer, and S.\u00a0Roweis (Eds.). Vol.\u00a020. Curran Associates , Inc .https:\/\/proceedings.neurips.cc\/paper\/ 2007 \/file\/013a006f03dbc5392effeb8f18fda755-Paper.pdf Ali Rahimi and Benjamin Recht. 2007. Random Features for Large-Scale Kernel Machines. In Advances in Neural Information Processing Systems, J.\u00a0Platt, D.\u00a0Koller, Y.\u00a0Singer, and S.\u00a0Roweis (Eds.). Vol.\u00a020. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper\/2007\/file\/013a006f03dbc5392effeb8f18fda755-Paper.pdf"},{"volume-title":"Gaussian Processes for Machine Learning","author":"Rasmussen Carl\u00a0Edward","key":"e_1_3_2_1_36_1","unstructured":"Carl\u00a0Edward Rasmussen and Chris Williams . 2006. Gaussian Processes for Machine Learning . MIT Press . Carl\u00a0Edward Rasmussen and Chris Williams. 2006. Gaussian Processes for Machine Learning. MIT Press."},{"key":"e_1_3_2_1_37_1","unstructured":"Alex Ray Joshua Achiam and Dario Amodei. 2019. Benchmarking safe exploration in deep reinforcement learning. (2019).  Alex Ray Joshua Achiam and Dario Amodei. 2019. Benchmarking safe exploration in deep reinforcement learning. (2019)."},{"key":"e_1_3_2_1_38_1","volume-title":"International Conference on Machine Learning. PMLR, 8020\u20138029","author":"Reddy Siddharth","year":"2020","unstructured":"Siddharth Reddy , Anca Dragan , Sergey Levine , Shane Legg , and Jan Leike . 2020 . Learning human objectives by evaluating hypothetical behavior . In International Conference on Machine Learning. PMLR, 8020\u20138029 . Siddharth Reddy, Anca Dragan, Sergey Levine, Shane Legg, and Jan Leike. 2020. Learning human objectives by evaluating hypothetical behavior. In International Conference on Machine Learning. PMLR, 8020\u20138029."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2017.2753460"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/CDC40024.2019.9030270"},{"volume-title":"Learning with kernels: support vector machines, regularization, optimization, and beyond","author":"Sch\u00f6lkopf Bernhard","key":"e_1_3_2_1_41_1","unstructured":"Bernhard Sch\u00f6lkopf , Alexander\u00a0 J Smola , Francis Bach , 2002. Learning with kernels: support vector machines, regularization, optimization, and beyond . MIT press . Bernhard Sch\u00f6lkopf, Alexander\u00a0J Smola, Francis Bach, 2002. Learning with kernels: support vector machines, regularization, optimization, and beyond. MIT press."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2728606.2728625"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-75225-7_5"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104448"},{"key":"e_1_3_2_1_45_1","unstructured":"Le Song Arthur Gretton and Carlos Guestrin. 2010. Nonparametric Tree Graphical Models. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research) Yee\u00a0Whye Teh and Mike Titterington (Eds.). Vol.\u00a09. PMLR Chia Laguna Resort Sardinia Italy 765\u2013772.  Le Song Arthur Gretton and Carlos Guestrin. 2010. Nonparametric Tree Graphical Models. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research) Yee\u00a0Whye Teh and Mike Titterington (Eds.). Vol.\u00a09. PMLR Chia Laguna Resort Sardinia Italy 765\u2013772."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553497"},{"key":"e_1_3_2_1_47_1","volume-title":"International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Vol.\u00a09035","author":"Esmaeil\u00a0Zadeh Soudjani Sadegh","year":"2015","unstructured":"Sadegh Esmaeil\u00a0Zadeh Soudjani , Caspar Gevaerts , and Alessandro Abate . 2015 . FAUST 2 : Formal Abstractions of Uncountable-STate STochastic Processes . In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Vol.\u00a09035 . Springer International Publishing, 272\u2013286. Sadegh Esmaeil\u00a0Zadeh Soudjani, Caspar Gevaerts, and Alessandro Abate. 2015. FAUST 2 : Formal Abstractions of Uncountable-STate STochastic Processes. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Vol.\u00a09035. Springer International Publishing, 272\u2013286."},{"volume-title":"Support Vector Machines","author":"Steinwart Ingo","key":"e_1_3_2_1_48_1","unstructured":"Ingo Steinwart and Andreas Christmann . 2008. Support Vector Machines . Springer Publishing Company, Inc orporated. Ingo Steinwart and Andreas Christmann. 2008. Support Vector Machines. Springer Publishing Company, Incorporated."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2010.08.006"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2019.2954102"},{"key":"e_1_3_2_1_51_1","volume-title":"2021 60th IEEE Conference on Decision and Control (CDC). 904\u2013911","author":"J.","year":"2021","unstructured":"Adam\u00a0 J. Thorpe and Meeko M.\u00a0K. Oishi. 2021. Stochastic Optimal Control via Hilbert Space Embeddings of Distributions . In 2021 60th IEEE Conference on Decision and Control (CDC). 904\u2013911 . https:\/\/doi.org\/10.1109\/CDC45484. 2021 .9682801 10.1109\/CDC45484.2021.9682801 Adam\u00a0J. Thorpe and Meeko M.\u00a0K. Oishi. 2021. Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. In 2021 60th IEEE Conference on Decision and Control (CDC). 904\u2013911. https:\/\/doi.org\/10.1109\/CDC45484.2021.9682801"},{"key":"e_1_3_2_1_52_1","volume-title":"\u00a0K. Oishi","author":"Thorpe J.","year":"2021","unstructured":"Adam\u00a0 J. Thorpe , Kendric\u00a0 R. Ortiz , and Meeko M . \u00a0K. Oishi . 2021 . Learning Approximate Forward Reachable Sets Using Separating Kernels. In Proceedings of the 3rd Conference on Learning for Dynamics and Control(Proceedings of Machine Learning Research), Ali Jadbabaie, John Lygeros, George\u00a0J. Pappas, Pablo A.\u00a0Parrilo, Benjamin Recht, Claire\u00a0J. Tomlin, and Melanie\u00a0N. Zeilinger (Eds.). Vol.\u00a0144. PMLR , 201\u2013212. Adam\u00a0J. Thorpe, Kendric\u00a0R. Ortiz, and Meeko M.\u00a0K. Oishi. 2021. Learning Approximate Forward Reachable Sets Using Separating Kernels. In Proceedings of the 3rd Conference on Learning for Dynamics and Control(Proceedings of Machine Learning Research), Ali Jadbabaie, John Lygeros, George\u00a0J. Pappas, Pablo A.\u00a0Parrilo, Benjamin Recht, Claire\u00a0J. Tomlin, and Melanie\u00a0N. Zeilinger (Eds.). Vol.\u00a0144. PMLR, 201\u2013212."},{"key":"e_1_3_2_1_53_1","volume-title":"SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. In 2021 60th IEEE Conference on Decision and Control (CDC). 5073\u20135079","author":"Thorpe J.","year":"2021","unstructured":"Adam\u00a0 J. Thorpe , Kendric\u00a0 R. Ortiz , and Meeko M . \u00a0K. Oishi. 2021 . SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. In 2021 60th IEEE Conference on Decision and Control (CDC). 5073\u20135079 . https:\/\/doi.org\/10.1109\/CDC45484. 2021 .9683169 10.1109\/CDC45484.2021.9683169 Adam\u00a0J. Thorpe, Kendric\u00a0R. Ortiz, and Meeko M.\u00a0K. Oishi. 2021. SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. In 2021 60th IEEE Conference on Decision and Control (CDC). 5073\u20135079. https:\/\/doi.org\/10.1109\/CDC45484.2021.9683169"},{"volume-title":"Approximate Stochastic Reachability for High Dimensional Systems. In 2021 American Control Conference (ACC). 1287\u20131293","author":"Thorpe J.","key":"e_1_3_2_1_54_1","unstructured":"Adam\u00a0 J. Thorpe , Vignesh Sivaramakrishnan , and Meeko M . \u00a0K. Oishi. 2021 . Approximate Stochastic Reachability for High Dimensional Systems. In 2021 American Control Conference (ACC). 1287\u20131293 . Adam\u00a0J. Thorpe, Vignesh Sivaramakrishnan, and Meeko M.\u00a0K. Oishi. 2021. Approximate Stochastic Reachability for High Dimensional Systems. In 2021 American Control Conference (ACC). 1287\u20131293."},{"key":"e_1_3_2_1_55_1","volume-title":"NNV: A Tool for Verification of Deep Neural Networks and Learning-Enabled Autonomous Cyber-Physical Systems. In International Conference on Computer-Aided Verification.","author":"Tran Hoang-Dung","year":"2020","unstructured":"Hoang-Dung Tran , Patrick Musau , Diego\u00a0Manzanas Lopez , Xiaodong Yang , Luan\u00a0Viet Nguyen , Weiming Xiang , and Taylor Johnson . 2020 . NNV: A Tool for Verification of Deep Neural Networks and Learning-Enabled Autonomous Cyber-Physical Systems. In International Conference on Computer-Aided Verification. Hoang-Dung Tran, Patrick Musau, Diego\u00a0Manzanas Lopez, Xiaodong Yang, Luan\u00a0Viet Nguyen, Weiming Xiang, and Taylor Johnson. 2020. NNV: A Tool for Verification of Deep Neural Networks and Learning-Enabled Autonomous Cyber-Physical Systems. In International Conference on Computer-Aided Verification."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3302504.3311809"},{"key":"e_1_3_2_1_57_1","volume-title":"Proceedings of The 24th International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Arindam Banerjee and Kenji Fukumizu (Eds.). Vol.\u00a0130","author":"Zhu Jia-Jie","year":"2021","unstructured":"Jia-Jie Zhu , Wittawat Jitkrittum , Moritz Diehl , and Bernhard Sch\u00f6lkopf . 2021 . Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation . In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Arindam Banerjee and Kenji Fukumizu (Eds.). Vol.\u00a0130 . PMLR, 280\u2013288. Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, and Bernhard Sch\u00f6lkopf. 2021. Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research), Arindam Banerjee and Kenji Fukumizu (Eds.). Vol.\u00a0130. PMLR, 280\u2013288."}],"event":{"name":"HSCC '22: 25th ACM International Conference on Hybrid Systems: Computation and Control","sponsor":["SIGBED ACM Special Interest Group on Embedded Systems"],"location":"Milan Italy","acronym":"HSCC '22"},"container-title":["25th ACM International Conference on Hybrid Systems: Computation and Control"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3501710.3519525","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3501710.3519525","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3501710.3519525","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3501710.3519525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:11Z","timestamp":1750183811000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3501710.3519525"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,4]]},"references-count":57,"alternative-id":["10.1145\/3501710.3519525","10.1145\/3501710"],"URL":"https:\/\/doi.org\/10.1145\/3501710.3519525","relation":{},"subject":[],"published":{"date-parts":[[2022,5,4]]},"assertion":[{"value":"2022-05-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}