Moshe Tennenholtz

Reinforcement Learning · 2001–2016

A researcher in the Science corpus: 7 papers; trusts 20 researchers and is trusted by 225 researchers here, as inferred from the citation graph.

Subfields

Whom Moshe Tennenholtz trusts overall

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

  1. Robert Leonard
  2. Michael L. Littman
  3. Leslie Pack Kaelbling
  4. Caroline Claus
  5. J. Urgen Schmidhuber
  6. Michael Kearns
  7. Ronen I. Brafman
  8. Richard S. Sutton
  9. Michael H. Bowling
  10. Tim Roughgarden

Who trusts Moshe Tennenholtz overall

  1. Michael L. Littman
  2. Alexander L. Strehl
  3. Todd Hester
  4. Peter Stone
  5. Lihong Li
  6. Andrew Critch
  7. Ian Osband
  8. J. Urgen Schmidhuber
  9. Emma Brunskill
  10. Pablo Hernandez-Leal

Papers from Moshe Tennenholtz's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Gradient-based learning applied to document recognition
  4. Reinforcement Learning: An Introduction
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Reinforcement Learning: A Survey
  7. Long Short-Term Memory
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. Learning Multiple Layers of Features from Tiny Images
  10. Asynchronous Methods for Deep Reinforcement Learning

Their papers