Tao Wang

Reinforcement Learning · with Bowling · 2005–2008

A researcher in the Science corpus: 5 papers; trusts 15 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

Whom Tao Wang trusts overall

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

  1. Richard S. Sutton
  2. Dimitri P. Bertsekas
  3. J. Nieuwenhuis
  4. Leemon C. Baird III
  5. Andrew Barto
  6. Malcolm J. A. Strens
  7. Radford M. Neal
  8. John N. Tsitsiklis
  9. Michael Kearns
  10. Peter S. Dayan

Who trusts Tao Wang overall

  1. Shangtong Zhang
  2. Bo Liu
  3. Ian Osband
  4. Arthur Guez
  5. Csaba Szepesvari
  6. Marc G. Bellemare
  7. Ofir Nachum
  8. Bo Dai
  9. Shimon Whiteson
  10. J. Kolter

Papers from Tao Wang's perspective

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

  1. Reinforcement Learning: An Introduction
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Residual Algorithms: Reinforcement Learning with Function Approximation
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Stable Function Approximation in Dynamic Programming
  8. Long Short-Term Memory
  9. Near-Optimal Reinforcement Learning in Polynomial Time
  10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers