843 citations · 1.2k across the 7 of their papers we have counts for
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cs.LG2019
When MAML Can Adapt Fast and How to Assist When It Cannot
Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
Model-Agnostic Meta-Learning (MAML) and its variants have achieved success in meta-learning tasks on many datasets and settings. On the other hand, we have just started to understa…
cs.RO2019
Toward Sim-to-Real Directional Semantic Grasping
Shariq Iqbal, Jonathan Tremblay, Thang To +6
We address the problem of directional semantic grasping, that is, grasping a specific object from a specific direction. We approach the problem using deep reinforcement learning vi…
cs.LG2019
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning
Shariq Iqbal, Fei Sha
Solving tasks with sparse rewards is one of the most important challenges in reinforcement learning. In the single-agent setting, this challenge is addressed by introducing intrins…