Jie Tang

Reinforcement Learning · with Abbeel · 2010–2012

A researcher in the Science corpus: 3 papers; trusts 26 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

Whom Jie Tang trusts overall

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

  1. Peter W. Glynn
  2. Jan Peters
  3. Ronald J. Williams
  4. David G. Lowe
  5. Sham M. Kakade
  6. Richard S. Sutton
  7. Stefan Schaal
  8. Andrew Y. Ng
  9. Jonathan Baxter
  10. Peter L. Bartlett

Who trusts Jie Tang overall

  1. Sergey Levine
  2. Liefeng Bo
  3. Shixiang Shane Gu
  4. George Tucker
  5. Vladlen Koltun
  6. Xiaofeng Ren
  7. Coline Devin
  8. Pieter Abbeel
  9. Trevor Darrell
  10. Anastasia Ioannidou

Papers from Jie Tang's perspective

Ordered by how strongly the researchers Jie Tang 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Learning Multiple Layers of Features from Tiny Images
  9. ImageNet Large Scale Visual Recognition Challenge
  10. GENERATIVE ADVERSARIAL NETS

Their papers