Hangtian Jia

Reinforcement Learning · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 37 citations into it
• Game & Decision Theory — 7 citations into it

Whom Hangtian Jia trusts overall

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

1. Jonathan Ho
2. Michael L. Littman
3. Geoffrey E. Hinton
4. Justin Fu

Papers from Hangtian Jia's perspective

Ordered by how strongly the researchers Hangtian Jia trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games (2021) — 20 citations
• Hierarchical Deep Multiagent Reinforcement Learning (2018) — 24 citations