Halit Bener Suay

Reinforcement Learning · 2011–2016

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 39 citations into it; #1,679 of 2,242 by trust here, #1,300 by citations
• Artificial Intelligence — 28 citations into it

Whom Halit Bener Suay trusts overall

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

1. Martin L. Puterman
2. Matthew E. Taylor
3. Richard S. Sutton
4. Gavin Adrian Rummery
5. Peter Stone
6. Stephen W. Carden
7. Andrew Y. Ng
8. Andrew Barto
9. Abdeslam Boularias
10. Mahesan Niranjan

Who trusts Halit Bener Suay overall

1. Todd Hester
2. W. B. Knox
3. Matej Vecerík
4. Allan Zhou
5. Daniel S. Brown
6. Olivier Pietquin
7. Baicen Xiao
8. Michael Gimelfarb

Papers from Halit Bener Suay's perspective

Ordered by how strongly the researchers Halit Bener Suay trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Markov Decision Processes: Discrete Stochastic Dynamic Programming
9. ImageNet: A large-scale hierarchical image database
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Learning from Demonstration for Shaping through Inverse Reinforcement Learning (2016) — 81 citations
• Reinforcement Learning from Demonstration through Shaping (2015) — 242 citations
• Integrating reinforcement learning with human demonstrations of varying ability (2011) — 165 citations