Yi Wan

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yi Wan trusts overall

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

  1. Richard S. Sutton
  2. Huizhen Yu
  3. Andrew Barto
  4. Doina Precup
  5. George Dimitri Konidaris
  6. Adam White
  7. Satinder Singh
  8. Dimitri P. Bertsekas
  9. Wesley Chung
  10. Csaba Szepesvari

Papers from Yi Wan's perspective

Ordered by how strongly the researchers Yi Wan 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. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  8. Long Short-Term Memory
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers