Yao Liu

Reinforcement Learning · with Brunskill · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 61 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Yao Liu trusts overall

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

  1. Richard S. Sutton
  2. R´emi Munos
  3. Sham M. Kakade
  4. Csaba Szepesvari
  5. Philip S. Thomas
  6. Damien Ernst
  7. Andrew Barto
  8. Martin A. Riedmiller
  9. Doina Precup
  10. Nan Jiang

Who trusts Yao Liu overall

  1. Tengyang Xie
  2. Ziyang Tang
  3. Nan Jiang
  4. Nathan Kallus
  5. Tianhe Yu
  6. Rafael Rafailov
  7. Maithra Raghu
  8. Aniruddh Raghu
  9. Paria Rashidinejad
  10. Masatoshi Uehara

Papers from Yao Liu's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Reinforcement Learning: An Introduction
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. ImageNet: A large-scale hierarchical image database
  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