Jeremy Dao

Reinforcement Learning · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 39 citations into it
• Artificial Intelligence — 33 citations into it
• Control and Systems Engineering — 21 citations into it
• Robotics & Control — 12 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Mechanical Engineering — 8 citations into it
• Computational Theory and Mathematics — 7 citations into it

Whom Jeremy Dao trusts overall

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

1. E. Todorov
2. Sham M. Kakade
3. Richard S. Sutton
4. Stéphane Ross
5. Jan Peters
6. John Schulman
7. Aravind Rajeswaran
8. Geoffrey E. Hinton
9. Dean A. Pomerleau
10. Sergey Levine

Papers from Jeremy Dao's perspective

Ordered by how strongly the researchers Jeremy Dao 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. Trust Region Policy Optimization (International Conference on Machine Learning)
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

• Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system (2018) — 66 citations
• Learning Locomotion Skills for Cassie: Iterative Design and Sim-to-Real (2019) — 175 citations