Georgios Theocharous
Reinforcement Learning · 2015–2020
A researcher in the Science corpus: 9 papers; trusts 64 researchers and is trusted by 52 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 97 citations into it; #323 of 2,242 by trust here, #676 by citations
- Artificial Intelligence — 75 citations into it; #5,939 of 35,345 by trust here, #8,283 by citations
- Management Science and Operations Research — 39 citations into it; #1,290 of 11,946 by trust here, #1,507 by citations
- Statistics and Probability — 20 citations into it
- Optimization & Training — 8 citations into it; #1,445 of 2,601 by trust here, #1,744 by citations
- Computational Theory and Mathematics — 7 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Computational Mechanics — 5 citations into it
Whom Georgios Theocharous trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Philip S. Thomas
- Doina Precup
- Andrew Barto
- Bradley Efron
- Stephen W. Carden
- Satinder Singh
- Geoffrey E. Hinton
- Sham M. Kakade
- George Dimitri Konidaris
Who trusts Georgios Theocharous overall
- Philip S. Thomas
- Nan Jiang
- Philip Thomas
- Thiago D. Simão
- Lihong Li
- Romain Laroche
- Emma Brunskill
- Ofir Nachum
- Josiah P. Hanna
- Yash Chandak
Papers from Georgios Theocharous's perspective
Ordered by how strongly the researchers Georgios Theocharous trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Reinforcement Learning: An Introduction
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
- Learning Multiple Layers of Features from Tiny Images
Their papers
- High-Confidence Off-Policy Evaluation (2015) — 320 citations
- Learning Action Representations for Reinforcement Learning (2019) — 193 citations
- Optimizing for the Future in Non-Stationary MDPs (2020) — 74 citations
- Towards Safe Policy Improvement for Non-Stationary MDPs (2020) — 46 citations
- Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing (2017) — 56 citations
- Personalized Ad Recommendation Systems for Life-Time Value Optimization with Guarantees (2015) — 125 citations
- High Confidence Policy Improvement (2015) — 200 citations
- Policy Evaluation Using the Ω-Return (2015) — 18 citations
- Policy Evaluation Using the \Omega -Return (2015)