Matthew Zucker

Reinforcement Learning · 2007–2013

A researcher in the Science corpus: 4 papers; trusts 21 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew Zucker trusts overall

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

  1. Nathan D. Ratliff
  2. Steven M. LaValle
  3. Ronald J. Williams
  4. James J. Kuffner Jr.
  5. Martin A. Zinkevich
  6. Leemon C. Baird III
  7. Radford M. Neal
  8. J. Bagnell
  9. Maxim Likhachev
  10. Lydia E. Kavraki

Who trusts Matthew Zucker overall

  1. Anca Dragan
  2. Harish Chaandar Ravichandar
  3. Dmitry Berenson
  4. Mrinal Kalakrishnan
  5. Ashesh Jain
  6. Pieter Abbeel
  7. J. Bagnell
  8. Sertac Karaman
  9. Jens Kober
  10. Jur van den Berg

Papers from Matthew Zucker's perspective

Ordered by how strongly the researchers Matthew Zucker 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. ImageNet: A large-scale hierarchical image database
  7. Long Short-Term Memory
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. GENERATIVE ADVERSARIAL NETS
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers