Yu-Han Chang

Reinforcement Learning · 2003

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yu-Han Chang trusts overall

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

  1. Richard S. Sutton
  2. Andrew Barto

Who trusts Yu-Han Chang overall

  1. Sven Gronauer
  2. Samuel J. Gershman
  3. Klaus-Jürgen Diepold
  4. Bijan Pesaran
  5. Paulina Varshavskaya
  6. Frans Adriaan Oliehoek
  7. Liviu Panait
  8. Sanjeevan Ahilan
  9. Chris Amato

Papers from Yu-Han Chang's perspective

Ordered by how strongly the researchers Yu-Han Chang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Reinforcement Learning: An Introduction
  2. Gradient-based learning applied to document recognition
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
  6. Learning internal representations by error propagation
  7. Residual Algorithms: Reinforcement Learning with Function Approximation
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. Markov Decision Processes: Discrete Stochastic Dynamic Programming
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers