Jee Won Park

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 15 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Jee Won Park trusts overall

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

1. Özgür Simsek
2. Andrew Barto
3. Richard S. Sutton
4. Marlos C. Machado
5. Miroslav Fiedler
6. A. Hinge
7. Doina Precup
8. Amy McGovern
9. Martin Stolle
10. Ishai Menache

Who trusts Jee Won Park overall

1. Martin Klissarov

Papers from Jee Won Park's perspective

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

1. Reinforcement Learning: An Introduction
2. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Markov Decision Processes: Discrete Stochastic Dynamic Programming
8. Asynchronous Methods for Deep Reinforcement Learning
9. Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
10. Long Short-Term Memory

Their papers

• Discovering Options for Exploration by Minimizing Cover Time (2019) — 60 citations