Daniel J. Mankowitz

58 papers A* 13A 2Misc 1Journal 36Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Nash Learning from Human Feedback. ICML Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Côme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot
2023	J	`jnl`	Faster sorting algorithms discovered using deep reinforcement learning. Nat. Daniel J. Mankowitz, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Cosmin Paduraru, Edouard Leurent, Shariq Iqbal, Jean-Baptiste Lespiau, Alex Ahern, Thomas Köppe, Kevin Millikin, Stephen Gaffney, Sophie Elster, Jackson Broshear, Chris Gamble, Kieran Milan, Robert Tung, Minjae Hwang, A. Taylan Cemgil, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert, Julian Schrittwieser, Demis Hassabis, Pushmeet Kohli, Martin A. Riedmiller, Oriol Vinyals, David Silver
2023	J	`jnl`	Nash Learning from Human Feedback. CoRR Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot
2023	J	`jnl`	Optimizing Memory Mapping Using Deep Reinforcement Learning. CoRR Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi, Phitchaya Mangpo Phothilimthana, Manish Purohit, Han Yang Tay, Ngân Vu, Miaosen Wang, Cosmin Paduraru, Edouard Leurent, Anton Zhernov, Julian Schrittwieser, Thomas Hubert, Robert Tung, Paula Kurylowicz, Kieran Milan, Oriol Vinyals, Daniel J. Mankowitz
2023	J	`jnl`	Towards practical reinforcement learning for tokamak magnetic control. CoRR Brendan D. Tracey, Andrea Michi, Yuri Chervonyi, Ian Davies, Cosmin Paduraru, Nevena Lazic, Federico Felici, Timo Ewalds, Craig Donner, Cristian Galperti, Jonas Buchli, Michael Neunert, Andrea Huber, Jonathan Evens, Paula Kurylowicz, Daniel J. Mankowitz, Martin A. Riedmiller, TCV Team
2023	A*	`conf`	Transformers Meet Directed Graphs. ICML Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
2023	J	`jnl`	Transformers Meet Directed Graphs. CoRR Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
2022	A*	`conf`	COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. ICLR Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez
2022	J	`jnl`	COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. CoRR Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez
2022	J	`jnl`	Competition-Level Code Generation with AlphaCode. CoRR Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals
2022	J	`jnl`	Controlling Commercial Cooling Systems Using Reinforcement Learning. CoRR Jerry Luo, Cosmin Paduraru, Octavian Voicu, Yuri Chervonyi, Scott Munns, Jerry Li, Crystal Qian, Praneet Dutta, Jared Quincy Davis, Ningjia Wu, Xingwei Yang, Chu-Ming Chang, Ted Li, Rob Rose, Mingyan Fan, Hootan Nakhost, Tinglin Liu, Brian Kirkman, Frank Altamura, Lee Cline, Patrick Tonker, Joel Gouker, Dave Uden, Warren Buddy Bryan, Jason Law, Deeni Fatiha, Neil Satra, Juliet Rothenberg, Molly Carlin, Satish Tallapaka, Sims Witherspoon, David Parish, Peter Dolan, Chenyu Zhao, Daniel J. Mankowitz
2022	J	`jnl`	MuZero with Self-competition for Rate Control in VP9 Video Compression. CoRR Amol Mandhane, Anton Zhernov, Maribeth Rauh, Chenjie Gu, Miaosen Wang, Flora Xue, Wendy Shang, Derek Pang, Rene Claus, Ching-Han Chiang, Cheng Chen, Jingning Han, Angie Chen, Daniel J. Mankowitz, Jackson Broshear, Julian Schrittwieser, Thomas Hubert, Oriol Vinyals, Timothy A. Mann
2021	Misc	`conf`	A Constrained Multi-Objective Reinforcement Learning Framework. CoRL Sandy H. Huang, Abbas Abdolmaleki, Giulia Vezzani, Philemon Brakel, Daniel J. Mankowitz, Michael Neunert, Steven Bohez, Yuval Tassa, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell
2021	A*	`conf`	Active Offline Policy Selection. NeurIPS Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
2021	J	`jnl`	Active Offline Policy Selection. CoRR Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
2021	A*	`conf`	Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
2021	J	`jnl`	Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2021	A*	`conf`	Discovering a set of policies for the worst case reward. ICLR Tom Zahavy, André Barreto, Daniel J. Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Singh
2021	J	`jnl`	Discovering a set of policies for the worst case reward. CoRR Tom Zahavy, André Barreto, Daniel J. Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Singh
2020	J	`jnl`	An empirical investigation of the challenges of real-world reinforcement learning. CoRR Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2020	J	`jnl`	Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
2020	J	`jnl`	Local Search for Policy Iteration in Continuous Control. CoRR Jost Tobias Springenberg, Nicolas Heess, Daniel J. Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin A. Riedmiller
2020	A*	`conf`	RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. CoRR Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin A. Riedmiller, Timothy A. Mann
2020	A*	`conf`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller
2019	A	`conf`	A Bayesian Approach to Robust Reinforcement Learning. UAI Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2019	J	`jnl`	A Bayesian Approach to Robust Reinforcement Learning. CoRR Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2019	J	`jnl`	Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces. CoRR Chen Tessler, Tom Zahavy, Deborah Cohen, Daniel J. Mankowitz, Shie Mannor
2019	J	`jnl`	Challenges of Real-World Reinforcement Learning. CoRR Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester
2019	—	`conf`	Reward Constrained Policy Optimization. ICLR (Poster) Chen Tessler, Daniel J. Mankowitz, Shie Mannor
2019	J	`jnl`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller
2019	J	`jnl`	Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. CoRR André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
2019	—	`conf`	Universal Successor Features Approximators. ICLR (Poster) Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Rémi Munos, David Silver, Tom Schaul
2018	A*	`conf`	Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning. NeurIPS Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor
2018	J	`jnl`	Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning. CoRR Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor
2018	—	`conf`	Learning How Not to Act in Text-based Games. ICLR (Workshop) Matan Haroush, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor
2018	A*	`conf`	Learning Robust Options. AAAI Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor
2018	J	`jnl`	Learning Robust Options. CoRR Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor
2018	J	`jnl`	Reward Constrained Policy Optimization. CoRR Chen Tessler, Daniel J. Mankowitz, Shie Mannor
2018	A	`conf`	Soft-Robust Actor-Critic Policy-Gradient. UAI Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2018	J	`jnl`	Soft-Robust Actor-Critic Policy-Gradient. CoRR Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2018	A*	`conf`	Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement. ICML André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
2018	J	`jnl`	Unicorn: Continual Learning with a Universal, Off-policy Agent. CoRR Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul
2018	J	`jnl`	Universal Successor Features Approximators. CoRR Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Rémi Munos, Hado van Hasselt, David Silver, Tom Schaul
2017	A*	`conf`	A Deep Hierarchical Approach to Lifelong Learning in Minecraft. AAAI Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor
2017	—	`conf`	Shallow Updates for Deep Reinforcement Learning. NIPS Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2017	J	`jnl`	Shallow Updates for Deep Reinforcement Learning. CoRR Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2017	J	`jnl`	Situationally Aware Options. CoRR Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2016	J	`jnl`	A Deep Hierarchical Approach to Lifelong Learning in Minecraft. CoRR Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor
2016	—	`conf`	Adaptive Skills Adaptive Partitions (ASAP). NIPS Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2016	J	`jnl`	Adaptive Skills, Adaptive Partitions (ASAP). CoRR Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2016	J	`jnl`	Iterative Hierarchical Optimization for Misspecified Problems (IHOMP). CoRR Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2016	J	`jnl`	Situational Awareness by Risk-Conscious Skills. CoRR Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
2015	J	`jnl`	Bootstrapping Skills. CoRR Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
2015	J	`jnl`	CFORB: Circular FREAK-ORB Visual Odometry. CoRR Daniel J. Mankowitz, Ehud Rivlin
2015	—	`conf`	Learning When to Switch between Skills in a High Dimensional Domain. AAAI Workshop: Learning for General Competency in Video Games Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor
2014	A*	`conf`	Time-Regularized Interrupting Options (TRIO). ICML Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor