137 citations · 527 across the 41 of their papers we have counts for
4 papers · 1 filter
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis +2
Learning how to act when there are many available actions in each state is a challenging task for Reinforcement Learning (RL) agents, especially when many of the actions are redund…
Deep Learning Reconstruction of Ultra-Short Pulses
Tom Zahavy, Alex Dikopoltsev, Oren Cohen +2
Ultra-short laser pulses with femtosecond to attosecond pulse duration are the shortest systematic events humans can create. Characterization (amplitude and phase) of these pulses…
Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies
Tom Zahavy, Avinatan Hasidim, Haim Kaplan +1
In this work, we provide theoretical guarantees for reward decomposition in deterministic MDPs. Reward decomposition is a special case of Hierarchical Reinforcement Learning, that…
Train on Validation: Squeezing the Data Lemon
Guy Tennenholtz, Tom Zahavy, Shie Mannor
Model selection on validation data is an essential step in machine learning. While the mixing of data between training and validation is considered taboo, practitioners often viola…