Matthew Jon Grounds

Reinforcement Learning · 2007

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 8 citations into it; #2,172 of 2,242 by trust here, #2,125 by citations

Whom Matthew Jon Grounds trusts overall

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

1. Richard S. Sutton
2. Satinder Singh
3. Tommi S. Jaakkola
4. Michael L. Littman
5. Andrew Barto
6. Ben J. A. Kröse

Who trusts Matthew Jon Grounds overall

1. David Silver
2. Tung-Long Vuong
3. Leonard Newnham
4. Do-Van Nguyen

Papers from Matthew Jon Grounds's perspective

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

1. Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Reinforcement Learning: An Introduction
6. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Asynchronous Methods for Deep Reinforcement Learning
10. Continuous control with deep reinforcement learning (International Conference on Learning Representations)

Their papers

• Parallel reinforcement learning with linear function approximation (2007) — 45 citations