Yi-Hsiang Chang

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Reinforcement Learning — 50 citations into it
• Management Science and Operations Research — 16 citations into it
• Optimization & Training — 9 citations into it

Whom Yi-Hsiang Chang trusts overall

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

1. Diederik P. Kingma
2. Richard S. Sutton
3. Geoffrey E. Hinton
4. Ronald J. Williams
5. Jimmy Ba
6. Sepp Hochreiter
7. Alex Krizhevsky
8. Yoshua Bengio
9. J. Urgen Schmidhuber
10. Michael L. Littman

Papers from Yi-Hsiang Chang's perspective

Ordered by how strongly the researchers Yi-Hsiang Chang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
9. Reinforcement Learning: An Introduction
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Deep Policy Inference Q-Network for Multi-Agent Systems (2017) — 93 citations
• Virtual-to-Real: Learning to Control in Visual Semantic Segmentation (2018) — 85 citations
• Diversity-Driven Exploration Strategy for Deep Reinforcement Learning (2018) — 147 citations