Jia-Hong Wu

Reinforcement Learning · 2007

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 5 citations into it

Whom Jia-Hong Wu trusts overall

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

1. Richard S. Sutton
2. Dimitri P. Bertsekas
3. Thomas Gärtner
4. Kurt Driessens
5. G. Tesauro
6. Sung Wook Yoon
7. Andrew Barto
8. J. Ramon

Who trusts Jia-Hong Wu overall

1. Martijn van Otterlo
2. Scott Sanner
3. Craig Boutilier

Papers from Jia-Hong Wu's perspective

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

1. Temporal Difference Learning and TD-Gammon
2. Neuro-Dynamic Programming
3. Learning to predict by the methods of temporal differences
4. Introduction to Reinforcement Learning
5. Graph kernels and Gaussian processes for relational reinforcement learning
6. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
7. FF-Replan: A Baseline for Probabilistic Planning (International Conference on Automated Planning and Scheduling)
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Linear Least-Squares algorithms for temporal difference learning
10. Stable Function Approximation in Dynamic Programming

Their papers

• Discovering Relational Domain Features for Probabilistic Planning (2007) — 15 citations