Kai-Fu Tang
Artificial Intelligence · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
- Reinforcement Learning — 8 citations into it
- Health Information Management — 6 citations into it
Whom Kai-Fu Tang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ron Kohavi
- Richard S. Sutton
- Volodymyr Mnih
- Andrew Barto
- Igor Kononenko
- Koray Kavukcuoglu
- Geoffrey E. Hinton
- David Silver
- Vinod Nair
- Alex Graves
Who trusts Kai-Fu Tang overall
- Hao-Cheng Kao
- Edward Y. Chang
- M. A. Ganaie
- Minghui Hu
- Chao Yu
- Meng-Hsi Wu
- Mohammad Tanveer
- Zhongyu Wei
- Ponnuthurai Nagaratnam Suganthan
- Jiming Liu
Papers from Kai-Fu Tang's perspective
Ordered by how strongly the researchers Kai-Fu Tang trusts endorse each paper. Same corpus, a different order for every researcher.
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- Rectified Linear Units Improve Restricted Boltzmann Machines
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Reinforcement Learning: An Introduction
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Context-Aware Symptom Checking for Disease Diagnosis Using Hierarchical Reinforcement Learning (2018) — 126 citations
- Artificial Intelligence in XPRIZE DeepQ Tricorder (2017) — 15 citations
- Inquire and Diagnose : Neural Symptom Checking Ensemble using Deep Reinforcement Learning (2016) — 84 citations