Tiancheng Yu
Reinforcement Learning · 2020
A researcher in the Science corpus: 3 papers; trusts 35 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 51 citations into it; #1,808 of 2,242 by trust here, #2,125 by citations
- Artificial Intelligence — 49 citations into it; #19,866 of 35,345 by trust here, #23,077 by citations
- Management Science and Operations Research — 33 citations into it; #6,135 of 11,946 by trust here, #6,563 by citations
- Computer Networks and Communications — 10 citations into it
- Statistical Learning Theory — 10 citations into it
- Game & Decision Theory — 5 citations into it
Whom Tiancheng Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chi Jin
- Michael L. Littman
- Sham M. Kakade
- Mohammad Gheshlaghi Azar
- Ronen I. Brafman
- Ian Osband
- Junling Hu
- R´emi Munos
- Yu Bai
- Richard S. Sutton
Who trusts Tiancheng Yu overall
Papers from Tiancheng Yu's perspective
Ordered by how strongly the researchers Tiancheng Yu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Reinforcement Learning: An Introduction
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Asynchronous Methods for Deep Reinforcement Learning
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Reward-Free Exploration for Reinforcement Learning (2020) — 237 citations
- Near-Optimal Reinforcement Learning with Self-Play (2020) — 149 citations
- A Sharp Analysis of Model-based Reinforcement Learning with Self-Play (2020) — 141 citations