Tom Zahavy - RankMe

75 papers A* 20A 2B 1Misc 1Journal 45Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions. CoRR Vivek Veeriah, Federico Barbero, Marcus Chiam, Xidong Feng, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Johan Obando-Ceron, Jiaxin Shi, Shaobo Hou, Satinder Singh, Nenad Tomasev, Tom Zahavy
2025	J	`jnl`	Generating Creative Chess Puzzles. CoRR Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Federico Barbero, Johan Obando-Ceron, Jiaxin Shi, Satinder Singh, Shaobo Hou, Nenad Tomasev, Tom Zahavy
2025	A*	`conf`	Mastering Board Games by External and Internal Planning with Language Models. ICML John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
2024	J	`jnl`	Mastering Board Games by External and Internal Planning with Language Models. CoRR John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
2023	J	`jnl`	APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT. CoRR Hadar Schreiber Galler, Tom Zahavy, Guillaume Desjardins, Alon Cohen
2023	A	`conf`	Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. GECCO Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag
2023	J	`jnl`	Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. CoRR Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag
2023	—	`conf`	Discovering Evolution Strategies via Meta-Black-Box Optimization. GECCO Companion Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag
2023	A*	`conf`	Discovering Evolution Strategies via Meta-Black-Box Optimization. ICLR Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag
2023	A*	`conf`	Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. ICLR Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh
2023	J	`jnl`	Diversifying AI: Towards Creative Chess with AlphaZero. CoRR Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh
2023	J	`jnl`	Optimism and Adaptivity in Policy Optimization. CoRR Veronica Chelu, Tom Zahavy, Arthur Guez, Doina Precup, Sebastian Flennerhag
2023	A*	`conf`	Optimistic Meta-Gradients. NeurIPS Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado Philip van Hasselt, András György, Satinder Singh
2023	J	`jnl`	Optimistic Meta-Gradients. CoRR Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado van Hasselt, András György, Satinder Singh
2023	J	`jnl`	POMRL: No-Regret Learning-to-Plan with Increasing Horizons. Trans. Mach. Learn. Res. Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy
2023	A*	`conf`	ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs. ICML Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy
2023	J	`jnl`	ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs. CoRR Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy
2022	A*	`conf`	Bootstrapped Meta-Learning. ICLR Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
2022	J	`jnl`	Discovering Evolution Strategies via Meta-Black-Box Optimization. CoRR Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dallibard, Chris Lu, Satinder Singh, Sebastian Flennerhag
2022	J	`jnl`	Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. CoRR Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh
2022	—	`conf`	Meta-Gradients in Non-Stationary Environments. CoLLAs Jelena Luketina, Sebastian Flennerhag, Yannick Schroecker, David Abel, Tom Zahavy, Satinder Singh
2022	J	`jnl`	Meta-Gradients in Non-Stationary Environments. CoRR Jelena Luketina, Sebastian Flennerhag, Yannick Schroecker, David Abel, Tom Zahavy, Satinder Singh
2022	A*	`conf`	Online Apprenticeship Learning. AAAI Lior Shani, Tom Zahavy, Shie Mannor
2022	J	`jnl`	POMRL: No-Regret Learning-to-Plan with Increasing Horizons. CoRR Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy
2022	A*	`conf`	Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. NeurIPS Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
2022	J	`jnl`	Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. CoRR Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
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`	Bootstrapped Meta-Learning. CoRR Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh
2021	J	`jnl`	Discovering Diverse Nearly Optimal Policies withSuccessor Features. CoRR Tom Zahavy, Brendan O'Donoghue, André Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh
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
2021	A*	`conf`	Discovery of Options via Meta-Learned Subgoals. NeurIPS Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	J	`jnl`	Discovery of Options via Meta-Learned Subgoals. CoRR Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	A*	`conf`	Emphatic Algorithms for Deep Reinforcement Learning. ICML Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
2021	J	`jnl`	Emphatic Algorithms for Deep Reinforcement Learning. CoRR Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
2021	J	`jnl`	Inverse reinforcement learning in contextual MDPs. Mach. Learn. Stav Belogolovsky, Philip Korsunsky, Shie Mannor, Chen Tessler, Tom Zahavy
2021	J	`jnl`	Online Apprenticeship Learning. CoRR Lior Shani, Tom Zahavy, Shie Mannor
2021	A*	`conf`	Online Limited Memory Neural-Linear Bandits with Likelihood Matching. ICML Ofir Nabati, Tom Zahavy, Shie Mannor
2021	J	`jnl`	Online Limited Memory Neural-Linear Bandits with Likelihood Matching. CoRR Ofir Nabati, Tom Zahavy, Shie Mannor
2021	A*	`conf`	Reward is enough for convex MDPs. NeurIPS Tom Zahavy, Brendan O'Donoghue, Guillaume Desjardins, Satinder Singh
2021	J	`jnl`	Reward is enough for convex MDPs. CoRR Tom Zahavy, Brendan O'Donoghue, Guillaume Desjardins, Satinder Singh
2020	A*	`conf`	A Self-Tuning Actor-Critic Algorithm. NeurIPS Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	A*	`conf`	Apprenticeship Learning via Frank-Wolfe. AAAI Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour
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	—	`conf`	Learning to Ask Medical Questions using Reinforcement Learning. MLHC Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan M. Krumholz
2020	J	`jnl`	Learning to Ask Medical Questions using Reinforcement Learning. CoRR Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan M. Krumholz
2020	B	`conf`	Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies. ALT Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour
2020	J	`jnl`	Self-Tuning Deep Reinforcement Learning. CoRR Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	A	`conf`	Unknown mixing times in apprenticeship and reinforcement learning. UAI Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour
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`	Apprenticeship Learning via Frank-Wolfe. CoRR Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour
2019	J	`jnl`	Average reward reinforcement learning with unknown mixing times. CoRR Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour
2019	J	`jnl`	Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching. CoRR Tom Zahavy, Shie Mannor
2019	J	`jnl`	Deep learning reconstruction of ultrashort pulses from 2D spatial intensity patterns recorded by an all-in-line system in a single-shot. CoRR Ron Ziv, Alex Dikopoltsev, Tom Zahavy, Ittai Rubinstein, Pavel Sidorenko, Oren Cohen, Mordechai Segev
2019	J	`jnl`	Inverse Reinforcement Learning in Contextual MDPs. CoRR Philip Korsunsky, Stav Belogolovsky, Tom Zahavy, Chen Tessler, Shie Mannor
2019	J	`jnl`	Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies. CoRR Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour
2018	J	`jnl`	Deep Learning Reconstruction of Ultra-Short Pulses. CoRR Tom Zahavy, Alex Dikopoltsev, Oren Cohen, Shie Mannor, Mordechai Segev
2018	—	`conf`	Ensemble Robustness and Generalization of Stochastic Deep Learning Algorithms. ICLR (Workshop) Tom Zahavy, Bingyi Kang, Alex Sivak, Jiashi Feng, Huan Xu, Shie Mannor
2018	J	`jnl`	Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies. CoRR Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour
2018	A*	`conf`	Is a Picture Worth a Thousand Words? A Deep Multi-Modal Architecture for Product Classification in E-Commerce. AAAI Tom Zahavy, Abhinandan Krishnan, Alessandro Magnani, Shie Mannor
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	J	`jnl`	Train on Validation: Squeezing the Data Lemon. CoRR Guy Tennenholtz, Tom Zahavy, Shie Mannor
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
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	J	`jnl`	Deep Reinforcement Learning Discovers Internal Models. CoRR Nir Baram, Tom Zahavy, Shie Mannor
2016	J	`jnl`	Ensemble Robustness of Deep Learning Algorithms. CoRR Jiashi Feng, Tom Zahavy, Bingyi Kang, Huan Xu, Shie Mannor
2016	A*	`conf`	Graying the black box: Understanding DQNs. ICML Tom Zahavy, Nir Ben-Zrihem, Shie Mannor
2016	J	`jnl`	Graying the black box: Understanding DQNs. CoRR Tom Zahavy, Nir Ben-Zrihem, Shie Mannor
2016	J	`jnl`	Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce. CoRR Tom Zahavy, Alessandro Magnani, Abhinandan Krishnan, Shie Mannor
2016	J	`jnl`	Visualizing Dynamics: from t-SNE to SEMI-MDPs. CoRR Nir Ben-Zrihem, Tom Zahavy, Shie Mannor
2014	Misc	`conf`	Sub-Nyquist sampling of OFDM signals for cognitive radios. ICASSP Tom Zahavy, Oran Shayer, Deborah Cohen, Alex Tolmachev, Yonina C. Eldar