Tom Zahavy

Orcid: 0009-0009-2309-922X

According to our database1, Tom Zahavy authored at least 46 papers between 2014 and 2023.

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Bibliography

2023
POMRL: No-Regret Learning-to-Plan with Increasing Horizons.
Trans. Mach. Learn. Res., 2023

APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT.
CoRR, 2023

Diversifying AI: Towards Creative Chess with AlphaZero.
CoRR, 2023

Optimism and Adaptivity in Policy Optimization.
CoRR, 2023

Optimistic Meta-Gradients.
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.
Proceedings of the International Conference on Machine Learning, 2023

Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Discovering Evolution Strategies via Meta-Black-Box Optimization.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022
Palm up: Playing in the Latent Manifold for Unsupervised Pretraining.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bootstrapped Meta-Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Gradients in Non-Stationary Environments.
Proceedings of the Conference on Lifelong Learning Agents, 2022

Online Apprenticeship Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Inverse reinforcement learning in contextual MDPs.
Mach. Learn., 2021

Discovering Diverse Nearly Optimal Policies withSuccessor Features.
CoRR, 2021

Reward is enough for convex MDPs.
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.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

Emphatic Algorithms for Deep Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Discovering a set of policies for the worst case reward.
Proceedings of the 9th International Conference on Learning Representations, 2021

Balancing Constraints and Rewards with Meta-Gradient D4PG.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Self-Tuning Deep Reinforcement Learning.
CoRR, 2020

Unknown mixing times in apprenticeship and reinforcement learning.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

A Self-Tuning Actor-Critic Algorithm.
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.
Proceedings of the Machine Learning for Healthcare Conference, 2020

Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies.
Proceedings of the Algorithmic Learning Theory, 2020

Apprenticeship Learning via Frank-Wolfe.
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.
CoRR, 2019

Average reward reinforcement learning with unknown mixing times.
CoRR, 2019

Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces.
CoRR, 2019

Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching.
CoRR, 2019

2018
Deep Learning Reconstruction of Ultra-Short Pulses.
CoRR, 2018

Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies.
CoRR, 2018

Train on Validation: Squeezing the Data Lemon.
CoRR, 2018

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning.
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.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning How Not to Act in Text-based Games.
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.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Shallow Updates for Deep Reinforcement Learning.
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.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Visualizing Dynamics: from t-SNE to SEMI-MDPs.
CoRR, 2016

Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce.
CoRR, 2016

Ensemble Robustness of Deep Learning Algorithms.
CoRR, 2016

Deep Reinforcement Learning Discovers Internal Models.
CoRR, 2016

Graying the black box: Understanding DQNs.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2014
Sub-Nyquist sampling of OFDM signals for cognitive radios.
Proceedings of the IEEE International Conference on Acoustics, 2014


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