Tom Zahavy

According to our database, Tom Zahavy authored at least 47 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT.

Hadar Schreiber Galler, Tom Zahavy, Guillaume Desjardins, Alon Cohen

CoRR, 2023

Diversifying AI: Towards Creative Chess with AlphaZero.

Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh

CoRR, 2023

Optimism and Adaptivity in Policy Optimization.

Veronica Chelu, Tom Zahavy, Arthur Guez, Doina Precup, Sebastian Flennerhag

CoRR, 2023

Optimistic Meta-Gradients.

Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado van Hasselt, András György, Satinder Singh

CoRR, 2023

Optimistic Meta-Gradients.

Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado Philip van Hasselt, András György, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs.

Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy

Proceedings of the International Conference on Machine Learning, 2023

Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality.

Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Discovering Evolution Strategies via Meta-Black-Box Optimization.

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

POMRL: No-Regret Learning-to-Plan with Increasing Horizons.

Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy

CoRR, 2022

Palm up: Playing in the Latent Manifold for Unsupervised Pretraining.

Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bootstrapped Meta-Learning.

Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Gradients in Non-Stationary Environments.

Jelena Luketina, Sebastian Flennerhag, Yannick Schroecker, David Abel, Tom Zahavy, Satinder Singh

Proceedings of the Conference on Lifelong Learning Agents, 2022

Online Apprenticeship Learning.

Lior Shani, Tom Zahavy, Shie Mannor

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Inverse reinforcement learning in contextual MDPs.

Stav Belogolovsky, Philip Korsunsky, Shie Mannor, Chen Tessler, Tom Zahavy

Mach. Learn., 2021

Discovering Diverse Nearly Optimal Policies withSuccessor Features.

Tom Zahavy, Brendan O'Donoghue, André Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh

CoRR, 2021

Reward is enough for convex MDPs.

Tom Zahavy, Brendan O'Donoghue, Guillaume Desjardins, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Discovery of Options via Meta-Learned Subgoals.

Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Limited Memory Neural-Linear Bandits with Likelihood Matching.

Ofir Nabati, Tom Zahavy, Shie Mannor

Proceedings of the 38th International Conference on Machine Learning, 2021

Emphatic Algorithms for Deep Reinforcement Learning.

Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt

Proceedings of the 38th International Conference on Machine Learning, 2021

Discovering a set of policies for the worst case reward.

Tom Zahavy, André Barreto, Daniel J. Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Singh

Proceedings of the 9th International Conference on Learning Representations, 2021

Balancing Constraints and Rewards with Meta-Gradient D4PG.

Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Self-Tuning Deep Reinforcement Learning.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

CoRR, 2020

Unknown mixing times in apprenticeship and reinforcement learning.

Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

A Self-Tuning Actor-Critic Algorithm.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Ask Medical Questions using Reinforcement Learning.

Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan M. Krumholz

Proceedings of the Machine Learning for Healthcare Conference, 2020

Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies.

Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour

Proceedings of the Algorithmic Learning Theory, 2020

Apprenticeship Learning via Frank-Wolfe.

Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep learning reconstruction of ultrashort pulses from 2D spatial intensity patterns recorded by an all-in-line system in a single-shot.

Ron Ziv, Alex Dikopoltsev, Tom Zahavy, Ittai Rubinstein, Pavel Sidorenko, Oren Cohen, Mordechai Segev

CoRR, 2019

Average reward reinforcement learning with unknown mixing times.

Tom Zahavy, Alon Cohen, Haim Kaplan, Yishay Mansour

CoRR, 2019

Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces.

Chen Tessler, Tom Zahavy, Deborah Cohen, Daniel J. Mankowitz, Shie Mannor

CoRR, 2019

Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching.

Tom Zahavy, Shie Mannor

CoRR, 2019

2018

Deep Learning Reconstruction of Ultra-Short Pulses.

Tom Zahavy, Alex Dikopoltsev, Oren Cohen, Shie Mannor, Mordechai Segev

CoRR, 2018

Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies.

Tom Zahavy, Avinatan Hassidim, Haim Kaplan, Yishay Mansour

CoRR, 2018

Train on Validation: Squeezing the Data Lemon.

Guy Tennenholtz, Tom Zahavy, Shie Mannor

CoRR, 2018

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning.

Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Ensemble Robustness and Generalization of Stochastic Deep Learning Algorithms.

Tom Zahavy, Bingyi Kang, Alex Sivak, Jiashi Feng, Huan Xu, Shie Mannor

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning How Not to Act in Text-based Games.

Matan Haroush, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor

Proceedings of the 6th International Conference on Learning Representations, 2018

Is a Picture Worth a Thousand Words? A Deep Multi-Modal Architecture for Product Classification in E-Commerce.

Tom Zahavy, Abhinandan Krishnan, Alessandro Magnani, Shie Mannor

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Shallow Updates for Deep Reinforcement Learning.

Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Deep Hierarchical Approach to Lifelong Learning in Minecraft.

Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Visualizing Dynamics: from t-SNE to SEMI-MDPs.

Nir Ben-Zrihem, Tom Zahavy, Shie Mannor

CoRR, 2016

Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce.

Tom Zahavy, Alessandro Magnani, Abhinandan Krishnan, Shie Mannor

CoRR, 2016

Ensemble Robustness of Deep Learning Algorithms.

Jiashi Feng, Tom Zahavy, Bingyi Kang, Huan Xu, Shie Mannor

CoRR, 2016

Deep Reinforcement Learning Discovers Internal Models.

Nir Baram, Tom Zahavy, Shie Mannor

CoRR, 2016

Graying the black box: Understanding DQNs.

Tom Zahavy, Nir Ben-Zrihem, Shie Mannor

Proceedings of the 33nd International Conference on Machine Learning, 2016

2014

Sub-Nyquist sampling of OFDM signals for cognitive radios.

Tom Zahavy, Oran Shayer, Deborah Cohen, Alex Tolmachev, Yonina C. Eldar

Proceedings of the IEEE International Conference on Acoustics, 2014