Timezone: »
Safe RL Panel Discussion
Animesh Garg · Marek Petrik · Shie Mannor · Claire Tomlin · Ugo Rosolia · Dylan Hadfield-Menell
Author Information
Animesh Garg (University of Toronto, Nvidia, Vector Institute)
I am a CIFAR AI Chair Assistant Professor of Computer Science at the University of Toronto, a Faculty Member at the Vector Institute, and Sr. Researcher at Nvidia. My current research focuses on machine learning for perception and control in robotics.
Marek Petrik (University of New Hampshire)
Shie Mannor (Technion)
Claire Tomlin (UC Berkeley)
Ugo Rosolia (Amazon)
Dylan Hadfield-Menell (UC Berkeley)
More from the Same Authors
-
2021 : Tutorial: Safe Learning for Decision Making »
Angela Schoellig · SiQi Zhou · Lukas Brunke · Animesh Garg · Melissa Greeff · Somil Bansal -
2021 Spotlight: RL for Latent MDPs: Regret Guarantees and a Lower Bound »
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor -
2021 : Unbiased Efficient Feature Counts for Inverse RL »
Gerard Donahue · Brendan Crowe · Marek Petrik · Daniel Brown -
2021 : Behavior Policy Search for Risk Estimators in Reinforcement Learning »
Elita Lobo · Marek Petrik · Dharmashankar Subramanian -
2021 : Maximum Likelihood Constraint Inference on Continuous State Spaces »
Kaylene Stocking · David McPherson · Robert Matthew · Claire Tomlin -
2021 : Reinforcement Learning in Reward-Mixing MDPs »
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor -
2021 : Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning »
Guy Tennenholtz · Assaf Hallak · Gal Dalal · Shie Mannor · Gal Chechik · Uri Shalit -
2021 : Latent Geodesics of Model Dynamics for Offline Reinforcement Learning »
Guy Tennenholtz · Nir Baram · Shie Mannor -
2021 : Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World Trifinger »
Arthur Allshire · Mayank Mittal · Varun Lodaya · Viktor Makoviychuk · Denys Makoviichuk · Felix Widmaier · Manuel Wuethrich · Stefan Bauer · Ankur Handa · Animesh Garg -
2021 : Learning Discrete Neural Reaction Class to Improve Retrosynthesis Prediction »
Théophile Gaudin · Animesh Garg · Alan Aspuru-Guzik -
2021 : Reinforcement Learning in Factored Action Spaces using Tensor Decompositions »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviichuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2021 : Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning »
Roy Zohar · Shie Mannor · Guy Tennenholtz -
2022 : DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles »
Peter Karkus · Boris Ivanovic · Shie Mannor · Marco Pavone -
2022 : ProgPrompt: Generating Situated Robot Task Plans using Large Language Models »
Ishika Singh · Valts Blukis · Arsalan Mousavian · Ankit Goyal · Danfei Xu · Jonathan Tremblay · Dieter Fox · Jesse Thomason · Animesh Garg -
2022 : Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs »
Benjamin Fuhrer · Yuval Shpigelman · Chen Tessler · Shie Mannor · Gal Chechik · Eitan Zahavi · Gal Dalal -
2022 : SoftTreeMax: Policy Gradient with Tree Search »
Gal Dalal · Assaf Hallak · Shie Mannor · Gal Chechik -
2022 : Learning Successor Feature Representations to Train Robust Policies for Multi-task Learning »
Melissa Mozifian · Dieter Fox · David Meger · Fabio Ramos · Animesh Garg -
2023 Poster: Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor »
Julien Grand-Clément · Marek Petrik -
2023 Poster: Percentile Criterion Optimization in Offline Reinforcement Learning »
Cyrus Cousins · Elita Lobo · Marek Petrik · Yair Zick -
2023 Poster: Policy Gradient for Rectangular Robust Markov Decision Processes »
Navdeep Kumar · Esther Derman · Matthieu Geist · Kfir Y. Levy · Shie Mannor -
2023 Poster: Individualized Dosing Dynamics via Neural Eigen Decomposition »
Stav Belogolovsky · Ido Greenberg · Danny Eytan · Shie Mannor -
2023 Poster: On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes »
Jia Lin Hau · Erick Delage · Mohammad Ghavamzadeh · Marek Petrik -
2023 Poster: Train Hard, Fight Easy: Robust Meta Reinforcement Learning »
Ido Greenberg · Shie Mannor · Gal Chechik · Eli Meirom -
2023 Poster: Optimization or Architecture: What Matters in Non-Linear Filtering? »
Ido Greenberg · Netanel Yannay · Shie Mannor -
2022 : Debate: Robotics for Good »
Karol Hausman · Katherine Driggs-Campbell · Luca Carlone · Sarah Dean · Matthew Johnson-Roberson · Animesh Garg -
2022 : Panel: Uncertainty-Aware Machine Learning for Robotics (Q&A 1) »
Georgia Chalvatzaki · Stefanie Tellex · Animesh Garg -
2022 Workshop: The Symbiosis of Deep Learning and Differential Equations II »
Michael Poli · Winnie Xu · Estefany Kelly Buchanan · Maryam Hosseini · Luca Celotti · Martin Magill · Ermal Rrapaj · Qiyao Wei · Stefano Massaroli · Patrick Kidger · Archis Joglekar · Animesh Garg · David Duvenaud -
2022 : Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs »
Benjamin Fuhrer · Yuval Shpigelman · Chen Tessler · Shie Mannor · Gal Chechik · Eitan Zahavi · Gal Dalal -
2022 Poster: Tractable Optimality in Episodic Latent MABs »
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor -
2022 Poster: Robust $\phi$-Divergence MDPs »
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann -
2022 Poster: Reinforcement Learning with a Terminator »
Guy Tennenholtz · Nadav Merlis · Lior Shani · Shie Mannor · Uri Shalit · Gal Chechik · Assaf Hallak · Gal Dalal -
2022 Poster: Finite Sample Analysis Of Dynamic Regression Parameter Learning »
Mark Kozdoba · Edward Moroshko · Shie Mannor · Yacov Crammer -
2022 Poster: Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning »
Guy Tennenholtz · Shie Mannor -
2022 Poster: Efficient Risk-Averse Reinforcement Learning »
Ido Greenberg · Yinlam Chow · Mohammad Ghavamzadeh · Shie Mannor -
2021 : Panel B: Safe Learning and Decision Making in Uncertain and Unstructured Environments »
Yisong Yue · J. Zico Kolter · Ivan Dario D Jimenez Rodriguez · Dragos Margineantu · Animesh Garg · Melissa Greeff -
2021 : Reinforcement Learning in Factored Action Spaces using Tensor Decompositions »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviichuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2021 : Theme B Introduction »
Animesh Garg -
2021 Workshop: Deployable Decision Making in Embodied Systems (DDM) »
Angela Schoellig · Animesh Garg · Somil Bansal · SiQi Zhou · Melissa Greeff · Lukas Brunke -
2021 Workshop: The Symbiosis of Deep Learning and Differential Equations »
Luca Celotti · Kelly Buchanan · Jorge Ortiz · Patrick Kidger · Stefano Massaroli · Michael Poli · Lily Hu · Ermal Rrapaj · Martin Magill · Thorsteinn Jonsson · Animesh Garg · Murtadha Aldeer -
2021 : Safely Learning Behaviors of Other Agents »
Claire Tomlin -
2021 : Safe RL Debate »
Sylvia Herbert · Animesh Garg · Emma Brunskill · Aleksandra Faust · Dylan Hadfield-Menell -
2021 : Ugo Rosolia »
Ugo Rosolia -
2021 : Ugo Rosolia »
Ugo Rosolia -
2021 : Shie Mannor »
Shie Mannor -
2021 : Shie Mannor »
Shie Mannor -
2021 Workshop: Safe and Robust Control of Uncertain Systems »
Ashwin Balakrishna · Brijen Thananjeyan · Daniel Brown · Marek Petrik · Melanie Zeilinger · Sylvia Herbert -
2021 Poster: Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers »
Mikita Dvornik · Isma Hadji · Konstantinos Derpanis · Animesh Garg · Allan Jepson -
2021 Poster: Twice regularized MDPs and the equivalence between robustness and regularization »
Esther Derman · Matthieu Geist · Shie Mannor -
2021 Poster: RL for Latent MDPs: Regret Guarantees and a Lower Bound »
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor -
2021 Poster: Sim and Real: Better Together »
Shirli Di-Castro · Dotan Di Castro · Shie Mannor -
2021 Poster: Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction »
Gal Dalal · Assaf Hallak · Steven Dalton · iuri frosio · Shie Mannor · Gal Chechik -
2021 Poster: Fast Algorithms for $L_\infty$-constrained S-rectangular Robust MDPs »
Bahram Behzadian · Marek Petrik · Chin Pang Ho -
2021 Poster: Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions »
Michael Poli · Stefano Massaroli · Luca Scimeca · Sanghyuk Chun · Seong Joon Oh · Atsushi Yamashita · Hajime Asama · Jinkyoo Park · Animesh Garg -
2021 Poster: Reinforcement Learning in Reward-Mixing MDPs »
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor -
2021 Poster: Dynamic Bottleneck for Robust Self-Supervised Exploration »
Chenjia Bai · Lingxiao Wang · Lei Han · Animesh Garg · Jianye Hao · Peng Liu · Zhaoran Wang -
2020 Poster: Causal Discovery in Physical Systems from Videos »
Yunzhu Li · Antonio Torralba · Anima Anandkumar · Dieter Fox · Animesh Garg -
2020 Poster: Curriculum By Smoothing »
Samarth Sinha · Animesh Garg · Hugo Larochelle -
2020 Spotlight: Curriculum By Smoothing »
Samarth Sinha · Animesh Garg · Hugo Larochelle -
2020 Poster: Consequences of Misaligned AI »
Simon Zhuang · Dylan Hadfield-Menell -
2020 Poster: Bayesian Robust Optimization for Imitation Learning »
Daniel S. Brown · Scott Niekum · Marek Petrik -
2020 Poster: Counterfactual Data Augmentation using Locally Factored Dynamics »
Silviu Pitis · Elliot Creager · Animesh Garg -
2020 Session: Orals & Spotlights Track 06: Dynamical Sys/Density/Sparsity »
Animesh Garg · Rose Yu -
2019 : Poster and Coffee Break 2 »
Karol Hausman · Kefan Dong · Ken Goldberg · Lihong Li · Lin Yang · Lingxiao Wang · Lior Shani · Liwei Wang · Loren Amdahl-Culleton · Lucas Cassano · Marc Dymetman · Marc Bellemare · Marcin Tomczak · Margarita Castro · Marius Kloft · Marius-Constantin Dinu · Markus Holzleitner · Martha White · Mengdi Wang · Michael Jordan · Mihailo Jovanovic · Ming Yu · Minshuo Chen · Moonkyung Ryu · Muhammad Zaheer · Naman Agarwal · Nan Jiang · Niao He · Nikolaus Yasui · Nikos Karampatziakis · Nino Vieillard · Ofir Nachum · Olivier Pietquin · Ozan Sener · Pan Xu · Parameswaran Kamalaruban · Paul Mineiro · Paul Rolland · Philip Amortila · Pierre-Luc Bacon · Prakash Panangaden · Qi Cai · Qiang Liu · Quanquan Gu · Raihan Seraj · Richard Sutton · Rick Valenzano · Robert Dadashi · Rodrigo Toro Icarte · Roshan Shariff · Roy Fox · Ruosong Wang · Saeed Ghadimi · Samuel Sokota · Sean Sinclair · Sepp Hochreiter · Sergey Levine · Sergio Valcarcel Macua · Sham Kakade · Shangtong Zhang · Sheila McIlraith · Shie Mannor · Shimon Whiteson · Shuai Li · Shuang Qiu · Wai Lok Li · Siddhartha Banerjee · Sitao Luan · Tamer Basar · Thinh Doan · Tianhe Yu · Tianyi Liu · Tom Zahavy · Toryn Klassen · Tuo Zhao · Vicenç Gómez · Vincent Liu · Volkan Cevher · Wesley Suttle · Xiao-Wen Chang · Xiaohan Wei · Xiaotong Liu · Xingguo Li · Xinyi Chen · Xingyou Song · Yao Liu · YiDing Jiang · Yihao Feng · Yilun Du · Yinlam Chow · Yinyu Ye · Yishay Mansour · · Yonathan Efroni · Yongxin Chen · Yuanhao Wang · Bo Dai · Chen-Yu Wei · Harsh Shrivastava · Hongyang Zhang · Qinqing Zheng · SIDDHARTHA SATPATHI · Xueqing Liu · Andreu Vall -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Adaptive Trust Region Policy Optimization: Convergence and Faster Rates of regularized MDPs »
Lior Shani · Yonathan Efroni · Shie Mannor -
2019 Workshop: Safety and Robustness in Decision-making »
Mohammad Ghavamzadeh · Shie Mannor · Yisong Yue · Marek Petrik · Yinlam Chow -
2019 Poster: Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs »
Marek Petrik · Reazul Hasan Russel -
2019 Poster: Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies »
Yonathan Efroni · Nadav Merlis · Mohammad Ghavamzadeh · Shie Mannor -
2019 Spotlight: Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies »
Yonathan Efroni · Nadav Merlis · Mohammad Ghavamzadeh · Shie Mannor -
2018 : Poster Session »
Sujay Sanghavi · Vatsal Shah · Yanyao Shen · Tianchen Zhao · Yuandong Tian · Tomer Galanti · Mufan Li · Gilad Cohen · Daniel Rothchild · Aristide Baratin · Devansh Arpit · Vagelis Papalexakis · Michael Perlmutter · Ashok Vardhan Makkuva · Pim de Haan · Yingyan Lin · Wanmo Kang · Cheolhyoung Lee · Hao Shen · Sho Yaida · Dan Roberts · Nadav Cohen · Philippe Casgrain · Dejiao Zhang · Tengyu Ma · Avinash Ravichandran · Julian Emilio Salazar · Bo Li · Davis Liang · Christopher Wong · Glen Bigan Mbeng · Animesh Garg -
2018 Poster: Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning »
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor -
2018 Poster: Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes »
Andrea Tirinzoni · Marek Petrik · Xiangli Chen · Brian Ziebart -
2018 Spotlight: Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning »
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor -
2018 Spotlight: Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes »
Andrea Tirinzoni · Marek Petrik · Xiangli Chen · Brian Ziebart -
2017 Poster: Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach »
Roel Dobbe · David Fridovich-Keil · Claire Tomlin -
2017 Poster: Rotting Bandits »
Nir Levine · Yacov Crammer · Shie Mannor -
2017 Poster: Countering Feedback Delays in Multi-Agent Learning »
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter W Glynn · Claire Tomlin -
2017 Poster: Shallow Updates for Deep Reinforcement Learning »
Nir Levine · Tom Zahavy · Daniel J Mankowitz · Aviv Tamar · Shie Mannor -
2016 Poster: Safe Policy Improvement by Minimizing Robust Baseline Regret »
Mohammad Ghavamzadeh · Marek Petrik · Yinlam Chow -
2016 Poster: Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games »
Maximilian Balandat · Walid Krichene · Claire Tomlin · Alexandre Bayen -
2016 Poster: Adaptive Skills Adaptive Partitions (ASAP) »
Daniel J Mankowitz · Timothy A Mann · Shie Mannor -
2015 : Between stochastic and adversarial: forecasting with online ARMA models »
Shie Mannor -
2015 Workshop: Machine Learning for (e-)Commerce »
Esteban Arcaute · Mohammad Ghavamzadeh · Shie Mannor · Georgios Theocharous -
2015 Poster: Online Learning for Adversaries with Memory: Price of Past Mistakes »
Oren Anava · Elad Hazan · Shie Mannor -
2015 Poster: Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach »
Yinlam Chow · Aviv Tamar · Shie Mannor · Marco Pavone -
2015 Poster: Policy Gradient for Coherent Risk Measures »
Aviv Tamar · Yinlam Chow · Mohammad Ghavamzadeh · Shie Mannor -
2015 Poster: Community Detection via Measure Space Embedding »
Mark Kozdoba · Shie Mannor -
2014 Workshop: From Bad Models to Good Policies (Sequential Decision Making under Uncertainty) »
Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor · Jeremie Mary · Laurent Orseau · Thomas Dietterich · Ronald Ortner · Peter Grünwald · Joelle Pineau · Raphael Fonteneau · Georgios Theocharous · Esteban D Arcaute · Christos Dimitrakakis · Nan Jiang · Doina Precup · Pierre-Luc Bacon · Marek Petrik · Aviv Tamar -
2014 Poster: "How hard is my MDP?" The distribution-norm to the rescue »
Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor -
2014 Poster: RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning »
Marek Petrik · Dharmashankar Subramanian -
2014 Poster: Robust Logistic Regression and Classification »
Jiashi Feng · Huan Xu · Shie Mannor · Shuicheng Yan -
2014 Spotlight: RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning »
Marek Petrik · Dharmashankar Subramanian -
2014 Oral: "How hard is my MDP?" The distribution-norm to the rescue »
Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor -
2013 Poster: Reinforcement Learning in Robust Markov Decision Processes »
Shiau Hong Lim · Huan Xu · Shie Mannor -
2013 Poster: Online PCA for Contaminated Data »
Jiashi Feng · Huan Xu · Shie Mannor · Shuicheng Yan -
2013 Poster: Learning Multiple Models via Regularized Weighting »
Daniel Vainsencher · Shie Mannor · Huan Xu -
2012 Poster: The Perturbed Variation »
Maayan Harel · Shie Mannor -
2011 Poster: From Bandits to Experts: On the Value of Side-Observations »
Shie Mannor · Ohad Shamir -
2011 Spotlight: From Bandits to Experts: On the Value of Side-Observations »
Shie Mannor · Ohad Shamir -
2011 Poster: Committing Bandits »
Loc X Bui · Ramesh Johari · Shie Mannor -
2010 Spotlight: Online Classification with Specificity Constraints »
Andrey Bernstein · Shie Mannor · Nahum Shimkin -
2010 Poster: Online Classification with Specificity Constraints »
Andrey Bernstein · Shie Mannor · Nahum Shimkin -
2010 Poster: Distributionally Robust Markov Decision Processes »
Huan Xu · Shie Mannor