Andrew Bagnell

Reinforcement Learning · 2001–2015

A researcher in the Science corpus: 3 papers; trusts 112 researchers and is trusted by 63 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 25 citations into it; #473 of 2,242 by trust here, #978 by citations
• Artificial Intelligence — 24 citations into it; #5,122 of 35,345 by trust here, #10,566 by citations
• Computer Vision and Pattern Recognition — 23 citations into it; #5,291 of 21,575 by trust here, #11,721 by citations
• Control and Systems Engineering — 11 citations into it
• Robotics & Control — 7 citations into it; #63 of 609 by trust here, #214 by citations
• Natural Language Processing — 5 citations into it

Whom Andrew Bagnell trusts overall

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

1. Stéphane Ross
2. J. Bagnell
3. Andrew Y. Ng
4. Nathan D. Ratliff
5. Brian D. Ziebart
6. Pieter Abbeel
7. Yoshua Bengio
8. Geoffrey E. Hinton
9. Yann LeCun
10. Daniel Munoz

Who trusts Andrew Bagnell overall

1. Brandon Packard
2. Marc Peter Deisenroth
3. Nathan D. Ratliff
4. Pieter Abbeel
5. Jens Behley
6. Devendra Singh Chaplot
7. Jan Peters
8. Takayuki Osa
9. J. Bagnell
10. Gerhard Neumann

Papers from Andrew Bagnell's perspective

Ordered by how strongly the researchers Andrew Bagnell 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Autonomous helicopter control using reinforcement learning policy search methods (2001) — 334 citations
• Contextual classification with functional Max-Margin Markov Networks (2009) — 363 citations
• An Invitation to Imitation (2015) — 91 citations