Richard Anthony Valenzano

Reinforcement Learning · 2013–2020

A researcher in the Science corpus: 3 papers; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 41 citations into it
• Artificial Intelligence — 30 citations into it
• Control and Systems Engineering — 8 citations into it
• Management Science and Operations Research — 8 citations into it

Whom Richard Anthony Valenzano trusts overall

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

1. Richard S. Sutton
2. Satinder Singh
3. Thomas G. Dietterich
4. Diederik P. Kingma
5. Andrew Y. Ng
6. Ronald E. Parr
7. Geoffrey E. Hinton
8. Hado van Hasselt
9. Stuart J. Russell
10. Andrew Barto

Who trusts Richard Anthony Valenzano overall

1. Noam Brown
2. Johannes Heinrich
3. Tuomas Sandholm

Papers from Richard Anthony Valenzano's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Long Short-Term Memory
6. Reinforcement Learning: An Introduction
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Human-level control through deep reinforcement learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning (2020) — 325 citations
• Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning (2018) — 359 citations
• Evaluating state-space abstractions in extensive-form games (2013) — 81 citations