324 citations · 2.8k across the 66 of their papers we have counts for
4 papers · 1 filter
MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks
Ariel Gordon, Elad Eban, Ofir Nachum +4
We present MorphNet, an approach to automate the design of neural network structures. MorphNet iteratively shrinks and expands a network, shrinking via a resource-weighted sparsify…
Trust-PCL: An Off-Policy Trust Region Method for Continuous Control
Ofir Nachum, Mohammad Norouzi, Kelvin Xu +1
Trust region methods, such as TRPO, are often used to stabilize policy optimization algorithms in reinforcement learning (RL). While current trust region strategies are effective f…
Learning to Remember Rare Events
Łukasz Kaiser, Ofir Nachum, Aurko Roy +1
Despite recent advances, memory-augmented deep neural networks are still limited when it comes to life-long and one-shot learning, especially in remembering rare events. We present…
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum, Mohammad Norouzi, Kelvin Xu +1
We establish a new connection between value and policy based reinforcement learning (RL) based on a relationship between softmax temporal value consistency and policy optimality un…