Tiong Yew Tang

Reinforcement Learning · 2014

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 6 citations into it

Whom Tiong Yew Tang trusts overall

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

1. Richard S. Sutton
2. Michael L. Littman
3. Christopher J. C. H. Watkins
4. Andrew Barto
5. Lucian Busoniu
6. Peter S. Dayan
7. Robert Babuška
8. Satinder Singh
9. Bruce S. McEwen
10. C. Pariante

Papers from Tiong Yew Tang's perspective

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

1. Reinforcement Learning: An Introduction
2. Learning to predict by the methods of temporal differences
3. Q-learning
4. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
5. Markov Decision Processes: Discrete Stochastic Dynamic Programming
6. ImageNet classification with deep convolutional neural networks
7. Gradient-based learning applied to document recognition
8. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Friend-or-Foe Q-learning in General-Sum Games

Their papers

• Reinforcement Learning in non-stationary environments: An intrinsically motivated stress based memory retrieval performance (SBMRP) model (2014) — 10 citations