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Mentoring Panel: Doina Precup, Deborah Raji, Anima Anandkumar, Angjoo Kanazawa and Sinead Williamson (moderator).
Doina Precup · Inioluwa Raji · Angjoo Kanazawa · Sinead A Williamson · Animashree Anandkumar
Author Information
Doina Precup (McGill University / DeepMind)
Inioluwa Raji (University of California, Berkeley)
Angjoo Kanazawa (UC Berkeley, Google Research)
Sinead A Williamson (University of Texas at Austin)
Animashree Anandkumar (Caltech)
More from the Same Authors
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2021 : Randomized Least Squares Policy Optimization »
Haque Ishfaq · Zhuoran Yang · Andrei Lupu · Viet Nguyen · Lewis Liu · Riashat Islam · Zhaoran Wang · Doina Precup -
2021 : Finite time analysis of temporal difference learning with linear function approximation: the tail averaged case »
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2022 : Physics-Informed Neural Operator for Learning Partial Differential Equations »
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2022 Workshop: Decision Awareness in Reinforcement Learning »
Evgenii Nikishin · Pierluca D'Oro · Doina Precup · Andre Barreto · Amir-massoud Farahmand · Pierre-Luc Bacon -
2022 Poster: Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error »
Scott Fujimoto · David Meger · Doina Precup · Ofir Nachum · Shixiang Gu -
2022 Poster: Diffusion Models for Adversarial Purification »
Weili Nie · Brandon Guo · Yujia Huang · Chaowei Xiao · Arash Vahdat · Animashree Anandkumar -
2022 Spotlight: Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error »
Scott Fujimoto · David Meger · Doina Precup · Ofir Nachum · Shixiang Gu -
2022 Spotlight: Diffusion Models for Adversarial Purification »
Weili Nie · Brandon Guo · Yujia Huang · Chaowei Xiao · Arash Vahdat · Animashree Anandkumar -
2022 Poster: Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification »
Leo Schwinn · Leon Bungert · An Nguyen · René Raab · Falk Pulsmeyer · Doina Precup · Bjoern Eskofier · Dario Zanca -
2022 Spotlight: Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification »
Leo Schwinn · Leon Bungert · An Nguyen · René Raab · Falk Pulsmeyer · Doina Precup · Bjoern Eskofier · Dario Zanca -
2022 Poster: Langevin Monte Carlo for Contextual Bandits »
Pan Xu · Hongkai Zheng · Eric Mazumdar · Kamyar Azizzadenesheli · Animashree Anandkumar -
2022 Poster: Understanding The Robustness in Vision Transformers »
Zhou Daquan · Zhiding Yu · Enze Xie · Chaowei Xiao · Animashree Anandkumar · Jiashi Feng · Jose M. Alvarez -
2022 Spotlight: Understanding The Robustness in Vision Transformers »
Zhou Daquan · Zhiding Yu · Enze Xie · Chaowei Xiao · Animashree Anandkumar · Jiashi Feng · Jose M. Alvarez -
2022 Spotlight: Langevin Monte Carlo for Contextual Bandits »
Pan Xu · Hongkai Zheng · Eric Mazumdar · Kamyar Azizzadenesheli · Animashree Anandkumar -
2021 : Invited Speaker: Animashree Anandkumar: Stability-aware reinforcement learning in dynamical systems »
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2021 Workshop: Workshop on Socially Responsible Machine Learning »
Chaowei Xiao · Animashree Anandkumar · Mingyan Liu · Dawn Song · Raquel Urtasun · Jieyu Zhao · Xueru Zhang · Cihang Xie · Xinyun Chen · Bo Li -
2021 Poster: Randomized Exploration in Reinforcement Learning with General Value Function Approximation »
Haque Ishfaq · Qiwen Cui · Viet Nguyen · Alex Ayoub · Zhuoran Yang · Zhaoran Wang · Doina Precup · Lin Yang -
2021 Spotlight: Randomized Exploration in Reinforcement Learning with General Value Function Approximation »
Haque Ishfaq · Qiwen Cui · Viet Nguyen · Alex Ayoub · Zhuoran Yang · Zhaoran Wang · Doina Precup · Lin Yang -
2021 Poster: Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards »
Susan Amin · Maziar Gomrokchi · Hossein Aboutalebi · Harsh Satija · Doina Precup -
2021 Poster: A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation »
Scott Fujimoto · David Meger · Doina Precup -
2021 Spotlight: A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation »
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2021 Spotlight: Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards »
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2021 Poster: Preferential Temporal Difference Learning »
Nishanth Anand · Doina Precup -
2021 Spotlight: Preferential Temporal Difference Learning »
Nishanth Anand · Doina Precup -
2020 : Panel Discussion »
Eric Eaton · Martha White · Doina Precup · Irina Rish · Harm van Seijen -
2020 Workshop: 4th Lifelong Learning Workshop »
Shagun Sodhani · Sarath Chandar · Balaraman Ravindran · Doina Precup -
2020 : Q&A: Anima Anandakumar »
Animashree Anandkumar · Jessica Forde -
2020 : Invited Talks: Anima Anandakumar »
Animashree Anandkumar -
2020 : Q&A: Deborah Raji »
Inioluwa Raji · Jessica Forde -
2020 : Invited Talk: Deborah Raji »
Inioluwa Raji -
2020 Poster: Interference and Generalization in Temporal Difference Learning »
Emmanuel Bengio · Joelle Pineau · Doina Precup -
2020 Poster: Invariant Causal Prediction for Block MDPs »
Amy Zhang · Clare Lyle · Shagun Sodhani · Angelos Filos · Marta Kwiatkowska · Joelle Pineau · Yarin Gal · Doina Precup -
2020 : Invited Talk: Doina Precup on Building Knowledge for AI Agents with Reinforcement Learning »
Doina Precup -
2020 Affinity Workshop: New In ML »
Zhen Xu · Sparkle Russell-Puleri · Zhengying Liu · Sinead A Williamson · Matthias W Seeger · Wei-Wei Tu · Samy Bengio · Isabelle Guyon -
2020 Workshop: WiML D&I Chairs Remarks: Sinead Williamson and Rachel Thomas »
Sinead A Williamson -
2019 Workshop: Workshop on Multi-Task and Lifelong Reinforcement Learning »
Sarath Chandar · Shagun Sodhani · Khimya Khetarpal · Tom Zahavy · Daniel J. Mankowitz · Shie Mannor · Balaraman Ravindran · Doina Precup · Chelsea Finn · Abhishek Gupta · Amy Zhang · Kyunghyun Cho · Andrei A Rusu · Facebook Rob Fergus -
2019 : Networking Lunch (provided) + Poster Session »
Abraham Stanway · Alex Robson · Aneesh Rangnekar · Ashesh Chattopadhyay · Ashley Pilipiszyn · Benjamin LeRoy · Bolong Cheng · Ce Zhang · Chaopeng Shen · Christian Schroeder · Christian Clough · Clement DUHART · Clement Fung · Cozmin Ududec · Dali Wang · David Dao · di wu · Dimitrios Giannakis · Dino Sejdinovic · Doina Precup · Duncan Watson-Parris · Gege Wen · George Chen · Gopal Erinjippurath · Haifeng Li · Han Zou · Herke van Hoof · Hillary A Scannell · Hiroshi Mamitsuka · Hongbao Zhang · Jaegul Choo · James Wang · James Requeima · Jessica Hwang · Jinfan Xu · Johan Mathe · Jonathan Binas · Joonseok Lee · Kalai Ramea · Kate Duffy · Kevin McCloskey · Kris Sankaran · Lester Mackey · Letif Mones · Loubna Benabbou · Lynn Kaack · Matthew Hoffman · Mayur Mudigonda · Mehrdad Mahdavi · Michael McCourt · Mingchao Jiang · Mohammad Mahdi Kamani · Neel Guha · Niccolo Dalmasso · Nick Pawlowski · Nikola Milojevic-Dupont · Paulo Orenstein · Pedram Hassanzadeh · Pekka Marttinen · Ramesh Nair · Sadegh Farhang · Samuel Kaski · Sandeep Manjanna · Sasha Luccioni · Shuby Deshpande · Soo Kim · Soukayna Mouatadid · Sunghyun Park · Tao Lin · Telmo Felgueira · Thomas Hornigold · Tianle Yuan · Tom Beucler · Tracy Cui · Volodymyr Kuleshov · Wei Yu · yang song · Ydo Wexler · Yoshua Bengio · Zhecheng Wang · Zhuangfang Yi · Zouheir Malki -
2019 Poster: Off-Policy Deep Reinforcement Learning without Exploration »
Scott Fujimoto · David Meger · Doina Precup -
2019 Oral: Off-Policy Deep Reinforcement Learning without Exploration »
Scott Fujimoto · David Meger · Doina Precup -
2018 Poster: StrassenNets: Deep Learning with a Multiplication Budget »
Michael Tschannen · Aran Khanna · Animashree Anandkumar -
2018 Oral: StrassenNets: Deep Learning with a Multiplication Budget »
Michael Tschannen · Aran Khanna · Animashree Anandkumar -
2018 Poster: Convergent Tree Backup and Retrace with Function Approximation »
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent -
2018 Oral: Convergent Tree Backup and Retrace with Function Approximation »
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent -
2017 Workshop: Reinforcement Learning Workshop »
Doina Precup · Balaraman Ravindran · Pierre-Luc Bacon