Jason Pazis

Reinforcement Learning · 2011–2017

A researcher in the Science corpus: 7 papers; trusts 60 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

Whom Jason Pazis trusts overall

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

  1. Sham M. Kakade
  2. Richard S. Sutton
  3. Alexander L. Strehl
  4. Michael L. Littman
  5. Teodor Mihai Moldovan
  6. Andrew Barto
  7. Damien Ernst
  8. Robert Tibshirani
  9. Leslie Pack Kaelbling
  10. Ronald E. Parr

Who trusts Jason Pazis overall

  1. Herke Van Hoof
  2. Chao Yu
  3. Ian Osband
  4. Sergey Levine
  5. Yuchen Cui
  6. Scott Niekum
  7. Erwan Lecarpentier
  8. Nan Jiang
  9. Justin Fu
  10. Rein Houthooft

Papers from Jason Pazis's perspective

Ordered by how strongly the researchers Jason Pazis 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Reinforcement Learning: An Introduction
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers