Eric Graves

Reinforcement Learning · 2018

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 31 citations into it; #1,352 of 2,242 by trust here, #2,063 by citations
• Artificial Intelligence — 13 citations into it; #18,519 of 35,345 by trust here, #29,412 by citations
• Management Science and Operations Research — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it; #6,086 of 12,182 by trust here, #8,756 by citations

Whom Eric Graves trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Hamid Reza Maei
3. Martha White
4. Longxin Lin
5. Andrew Barto
6. Huizhen Yu
7. Ian H. Witten
8. David Silver
9. Timothy P. Lillicrap
10. Doina Precup

Who trusts Eric Graves overall

1. Shangtong Zhang
2. Sergey Levine
3. Bo Liu
4. Yao Liu
5. Shimon Whiteson
6. Wesley A. Suttle

Papers from Eric Graves's perspective

Ordered by how strongly the researchers Eric Graves trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Human-level control through deep reinforcement learning
5. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
6. Reinforcement Learning: An Introduction
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
9. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
10. Long Short-Term Memory

Their papers

• An Off-policy Policy Gradient Theorem Using Emphatic Weightings (2018) — 76 citations