John W. Roberts

Reinforcement Learning · 2005–2013

A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 27 citations into it; #1,817 of 2,242 by trust here, #1,932 by citations
• Control and Systems Engineering — 17 citations into it; #6,922 of 8,257 by trust here, #3,682 by citations
• Artificial Intelligence — 10 citations into it; #22,861 of 35,345 by trust here, #22,463 by citations
• Computational Theory and Mathematics — 6 citations into it; #10,286 of 12,182 by trust here, #5,465 by citations
• Aerospace Engineering — 5 citations into it; #4,699 of 6,421 by trust here, #6,012 by citations
• Optimization & Training — 5 citations into it

Whom John W. Roberts trusts overall

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

1. Ronald J. Williams
2. Pieter Abbeel
3. Richard S. Sutton
4. Russ Tedrake
5. Andrew Y. Ng
6. Andrew Barto
7. Shun-ichi Amari
8. Jonathan Baxter
9. Leslie Pack Kaelbling
10. Jan Peters

Who trusts John W. Roberts overall

1. Olivier Sigaud
2. Sebastian Trimpe
3. Jan Peters
4. Jeremy H. Gillula
5. Christian Cierpka
6. Amir-massoud Farahmand
7. Jens Kober
8. Claire Jennifer Tomlin
9. Erik Talvitie
10. Alexander Millane

Papers from John W. Roberts's perspective

Ordered by how strongly the researchers John W. Roberts 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. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Reinforcement learning with misspecified model classes (2013) — 43 citations
• Feedback controller parameterizations for Reinforcement Learning (2011) — 35 citations
• LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification (2010) — 520 citations
• Motor Learning at Intermediate Reynolds Number: Experiments with Policy Gradient on the Flapping Flight of a Rigid Wing (2010) — 24 citations
• Three-dimensional fluorescent particle tracking at micron-scale using a single camera (2005) — 146 citations