Steven Wu

Reinforcement Learning · 2021

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 19 citations into it
• Artificial Intelligence — 16 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it

Whom Steven Wu trusts overall

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

1. Stéphane Ross
2. J. Bagnell
3. Nathan D. Ratliff
4. G. Tesauro
5. Dean A. Pomerleau
6. Sergey Levine
7. Yoav Freund
8. Brian D. Ziebart

Papers from Steven Wu's perspective

Ordered by how strongly the researchers Steven Wu 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Proximal Policy Optimization Algorithms (arXiv.org)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap (2021) — 95 citations