Michael Schapira

Computer Networks and Communications · with Godfrey · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Networks and Communications — 22 citations into it
• Artificial Intelligence — 12 citations into it
• Reinforcement Learning — 12 citations into it
• Electrical and Electronic Engineering — 10 citations into it

Whom Michael Schapira trusts overall

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

1. Keith Winstein
2. John Schulman
3. Richard S. Sutton

Papers from Michael Schapira's perspective

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

1. Reinforcement Learning: An Introduction
2. Proximal Policy Optimization Algorithms (arXiv.org)
3. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
4. Trust Region Policy Optimization (International Conference on Machine Learning)
5. Mastering the game of Go with deep neural networks and tree search
6. Mastering the game of Go without human knowledge
7. ImageNet classification with deep convolutional neural networks
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
10. Planning and Acting in Partially Observable Stochastic Domains

Their papers

• A Deep Reinforcement Learning Perspective on Internet Congestion Control (2019) — 407 citations
• PCC Vivace: Online-Learning Congestion Control (2018) — 418 citations