Hao-Cheng Kao

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Reinforcement Learning — 6 citations into it

Whom Hao-Cheng Kao trusts overall

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

1. Kai-Fu Tang
2. Vinod Nair
3. Volodymyr Mnih
4. Geoffrey E. Hinton
5. Igor Kononenko
6. Edward Y. Chang
7. Richard S. Sutton
8. Ron Kohavi
9. Alistair E. W. Johnson
10. Koray Kavukcuoglu

Papers from Hao-Cheng Kao's perspective

Ordered by how strongly the researchers Hao-Cheng Kao trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet: A large-scale hierarchical image database
2. Rectified Linear Units Improve Restricted Boltzmann Machines
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Reinforcement Learning: An Introduction
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Playing Atari with Deep Reinforcement Learning (arXiv.org)
9. Long Short-Term Memory
10. Caffe: Convolutional Architecture for Fast Feature Embedding

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