Ziyang Tang
Reinforcement Learning · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 111 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 75 citations into it; #765 of 2,242 by trust here, #1,028 by citations
- Artificial Intelligence — 50 citations into it
- Management Science and Operations Research — 37 citations into it; #2,141 of 11,946 by trust here, #2,185 by citations
- Statistics and Probability — 22 citations into it
- Statistical Learning Theory — 12 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Computational Theory and Mathematics — 8 citations into it
- Computer Networks and Communications — 8 citations into it; #1,761 of 9,886 by trust here, #1,744 by citations
Whom Ziyang Tang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lihong Li
- Nathan Kallus
- Martin L. Puterman
- Tim Hesterberg
- Jun S. Liu
- Bo Dai
- Philip S. Thomas
- Richard S. Sutton
- Nan Jiang
- William T. B. Uther
Who trusts Ziyang Tang overall
- Nathan Kallus
- Masatoshi Uehara
- Nan Jiang
- Shangtong Zhang
- Ofir Nachum
- Bo Dai
- Shangding Gu
- Jiawei Huang
- Mengjiao Yang
- Andrea Zanette
Papers from Ziyang Tang's perspective
Ordered by how strongly the researchers Ziyang Tang 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Reinforcement Learning: An Introduction
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- GENERATIVE ADVERSARIAL NETS