Istvan Szita

Reinforcement Learning · 2002–2012

A researcher in the Science corpus: 7 papers; trusts 41 researchers and is trusted by 75 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 48 citations into it; #279 of 2,242 by trust here, #916 by citations
• Artificial Intelligence — 40 citations into it; #4,692 of 35,345 by trust here, #9,968 by citations
• Management Science and Operations Research — 16 citations into it; #10,188 of 11,946 by trust here, #7,262 by citations
• Statistical Learning Theory — 8 citations into it; #314 of 1,038 by trust here, #488 by citations
• Game & Decision Theory — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it; #8,914 of 12,182 by trust here, #7,501 by citations
• Economics and Econometrics — 5 citations into it
• Sociology and Political Science — 5 citations into it; #4,934 of 22,756 by trust here, #11,144 by citations

Whom Istvan Szita trusts overall

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

1. Michael L. Littman
2. Alexander L. Strehl
3. Richard S. Sutton
4. Ronen I. Brafman
5. Michael Kearns
6. Dimitri P. Bertsekas
7. Andrew Barto
8. Satinder Singh
9. Sham M. Kakade
10. Malcolm J. A. Strens

Who trusts Istvan Szita overall

1. Tor Lattimore
2. Christoph Dann
3. Brendan O'Donoghue
4. Dimitri P. Bertsekas
5. Csaba Szepesvari
6. Lihong Li
7. John Schulman
8. W. B. Knox
9. Karthik Narasimhan
10. Jason Pazis

Papers from Istvan Szita's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Reinforcement Learning: An Introduction
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. ImageNet: A large-scale hierarchical image database
9. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Learning Tetris Using the Noisy Cross-Entropy Method (2006) — 259 citations
• The many faces of optimism: a unifying approach (2008) — 105 citations
• Reinforcement Learning in Games (2012) — 73 citations
• Exploring compact reinforcement-learning representations with linear regression (2009) — 120 citations
• Monte-Carlo Tree Search: A New Framework for Game AI (2008) — 465 citations
• Model-based reinforcement learning with nearly tight exploration complexity bounds (2010) — 161 citations
• MDPs: Learning in Varying Environments (2002)