Nadav Merlis

Reinforcement Learning · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 48 citations into it; #1,798 of 2,242 by trust here, #1,609 by citations
• Artificial Intelligence — 41 citations into it; #26,731 of 35,345 by trust here, #19,018 by citations
• Management Science and Operations Research — 18 citations into it; #8,810 of 11,946 by trust here, #4,430 by citations
• Natural Language Processing — 10 citations into it

Whom Nadav Merlis trusts overall

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

1. Ronald J. Williams
2. Richard S. Sutton
3. Martin L. Puterman
4. Eitan Altman
5. Shipra Agrawal
6. Geoffrey E. Hinton
7. Andrew Barto
8. Aditya Gopalan
9. Béatrice Laurent
10. Yasin Abbasi-Yadkori

Who trusts Nadav Merlis overall

1. Prithviraj Ammanabrolu
2. Matthew J. Hausknecht

Papers from Nadav Merlis's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Reinforcement Learning: An Introduction
7. Attention is All you Need (Neural Information Processing Systems)
8. Human-level control through deep reinforcement learning
9. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
10. ImageNet: A large-scale hierarchical image database

Their papers

• Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning (2018) — 218 citations
• Reinforcement Learning with Trajectory Feedback (2020) — 49 citations