Riad Akrour

Reinforcement Learning · 2011–2018

A researcher in the Science corpus: 5 papers; trusts 69 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 81 citations into it; #555 of 2,242 by trust here, #738 by citations
• Artificial Intelligence — 75 citations into it; #12,097 of 35,345 by trust here, #19,018 by citations
• Control and Systems Engineering — 26 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Optimization & Training — 14 citations into it
• Management Science and Operations Research — 13 citations into it
• Robotics & Control — 12 citations into it
• Computational Theory and Mathematics — 11 citations into it

Whom Riad Akrour trusts overall

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

1. Richard S. Sutton
2. Andrew Y. Ng
3. Andrew Barto
4. Thorsten Joachims
5. Jan Peters
6. Geoffrey E. Hinton
7. John M. Henderson
8. Eric Brochu
9. Yann LeCun
10. Yoshua Bengio

Who trusts Riad Akrour overall

1. Christian Wirth
2. Róbert Istvan Busa-Fekete
3. Jan Leike
4. Ellen R. Novoseller
5. Marc Schoenauer
6. Paul Christiano
7. Johannes Fürnkranz
8. Chao Yu
9. Balázs Szörényi
10. Aldo Pacchiano

Papers from Riad Akrour's perspective

Ordered by how strongly the researchers Riad Akrour 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. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Reinforcement Learning: An Introduction
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• APRIL: Active Preference-learning based Reinforcement Learning (2012) — 126 citations
• Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences (2018) — 23 citations
• A Survey of Preference-Based Reinforcement Learning Methods (2017) — 475 citations
• Programming by Feedback (2014) — 72 citations
• Preference-Based Policy Learning (2011)