Noga H. Rotman

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 12 citations into it
• Artificial Intelligence — 11 citations into it
• Computer Networks and Communications — 8 citations into it

Whom Noga H. Rotman trusts overall

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

1. John Schulman
2. Richard S. Sutton
3. Keith Winstein
4. Andrew Barto
5. Bernhard Schölkopf
6. Sergey Levine
7. Horia Mania
8. Sangtae Ha
9. David Silver
10. Pieter Abbeel

Papers from Noga H. Rotman's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Reinforcement Learning: An Introduction
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Proximal Policy Optimization Algorithms (arXiv.org)
10. Trust Region Policy Optimization (International Conference on Machine Learning)

Their papers

• A Deep Reinforcement Learning Perspective on Internet Congestion Control (2019) — 407 citations