Yung Yi

Reinforcement Learning · 2004–2020

A researcher in the Science corpus: 9 papers; trusts 72 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

Whom Yung Yi trusts overall

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

  1. M. Kodialam
  2. Jakob N. Foerster
  3. Tabish Rashid
  4. Steven H. Low
  5. T. Nandagopal
  6. Geoffrey E. Hinton
  7. Richard S. Sutton
  8. Ross B. Girshick
  9. Srisankar S. Kunniyur
  10. Ming Tan

Who trusts Yung Yi overall

  1. Xiaojun Lin
  2. Ness B. Shroff
  3. Mosharaf Chowdhury
  4. Long Gong
  5. Jens Lischka
  6. Atilla Eryilmaz
  7. Tonghan Wang
  8. Shigang Chen
  9. Ines Houidi
  10. Kyunghwan Son

Papers from Yung Yi's perspective

Ordered by how strongly the researchers Yung Yi 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. ImageNet: A large-scale hierarchical image database
  4. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Reinforcement Learning: An Introduction
  9. Human-level control through deep reinforcement learning
  10. Learning Multiple Layers of Features from Tiny Images

Their papers