Özgür Simsek

Reinforcement Learning · 2004–2008

A researcher in the Science corpus: 5 papers; trusts 31 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 42 citations into it; #396 of 2,242 by trust here, #756 by citations
• Artificial Intelligence — 16 citations into it; #4,765 of 35,345 by trust here, #8,283 by citations
• Computational Theory and Mathematics — 6 citations into it; #1,302 of 12,182 by trust here, #1,463 by citations

Whom Özgür Simsek trusts overall

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

1. Richard S. Sutton
2. Andrew Barto
3. Doina Precup
4. Satinder Singh
5. Ronald E. Parr
6. Bernhard Hengst
7. Amy McGovern
8. Longxin Lin
9. Michael O. Duff
10. Thomas G. Dietterich

Who trusts Özgür Simsek overall

1. George Dimitri Konidaris
2. Andrew Barto
3. J. Urgen Schmidhuber
4. Yuu Jinnai
5. Peter S. Dayan
6. Matthew Botvinick
7. Bruno Castro da Silva
8. Doina Precup
9. Sridhar Mahadevan
10. Sergey Levine

Papers from Özgür Simsek's perspective

Ordered by how strongly the researchers Özgür Simsek 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. Reinforcement Learning: An Introduction
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Identifying useful subgoals in reinforcement learning by local graph partitioning (2005) — 305 citations
• An intrinsic reward mechanism for efficient exploration (2006) — 136 citations
• Using relative novelty to identify useful temporal abstractions in reinforcement learning (2004) — 258 citations
• Skill Characterization Based on Betweenness (2008) — 186 citations
• Intrinsic Motivation For Reinforcement Learning Systems (2005)