Feng Wu

Reinforcement Learning · with Bai · 2015

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 18 citations into it
• Artificial Intelligence — 12 citations into it

Whom Feng Wu trusts overall

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

1. Andrew Barto
2. Martin L. Puterman
3. Thomas G. Dietterich
4. Richard S. Sutton
5. Sridhar Mahadevan
6. Levente Kocsis
7. Michael Kearns
8. David Andre
9. Eric A. Hansen
10. Blai Bonet

Papers from Feng Wu's perspective

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

1. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
2. ImageNet classification with deep convolutional neural networks
3. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Markov Decision Processes: Discrete Stochastic Dynamic Programming
6. Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning to Act Using Real-Time Dynamic Programming
10. Recent Advances in Hierarchical Reinforcement Learning

Their papers

• Online Planning for Large Markov Decision Processes with Hierarchical Decomposition (2015) — 19 citations