Laëtitia Matignon

Reinforcement Learning · 2007–2012

A researcher in the Science corpus: 4 papers; trusts 31 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

Whom Laëtitia Matignon trusts overall

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

  1. Ming Tan
  2. Richard S. Sutton
  3. Craig Boutilier
  4. Christopher J. C. H. Watkins
  5. Martin Lauer
  6. Liviu Panait
  7. Andrew Barto
  8. Michael H. Bowling
  9. Kagan Tumer
  10. Caroline Claus

Who trusts Laëtitia Matignon overall

  1. Gregory Palmer
  2. Xueguang Lyu
  3. Afshin Oroojlooyjadid
  4. Chris Amato
  5. Xueguang Lu
  6. Karl Tuyls
  7. Shayegan Omidshafiei
  8. Pablo Hernandez-Leal
  9. Davood Hajinezhad
  10. Sven Gronauer

Papers from Laëtitia Matignon's perspective

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

  1. Reinforcement Learning: An Introduction
  2. ImageNet classification with deep convolutional neural networks
  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: A Survey
  7. Long Short-Term Memory
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Markov Games as a Framework for Multi-Agent Reinforcement Learning

Their papers