Bill Hibbard

Reinforcement Learning · 2011–2015

A researcher in the Science corpus: 3 papers; trusts 24 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Bill Hibbard trusts overall

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

  1. Seth Lloyd
  2. Richard S. Sutton
  3. S. Omohundro
  4. Andrew Barto
  5. Mark B. Ring
  6. Dan Dewey
  7. J. Urgen Schmidhuber
  8. Marcus Hutter
  9. Linus Gisslén
  10. Radford M. Neal

Who trusts Bill Hibbard overall

  1. Tom Everitt
  2. Ben Goertzel
  3. Noah Goodall
  4. Marcus Hutter
  5. Stuart J. Russell
  6. Roman V Yampolskiy
  7. Ramana Kumar
  8. Victoria Krakovna
  9. Shane Legg
  10. Dan Dewey

Papers from Bill Hibbard's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. Gradient-based learning applied to document recognition
  3. ImageNet classification with deep convolutional neural networks
  4. Reinforcement Learning: An Introduction
  5. Long Short-Term Memory
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Attention is All you Need (Neural Information Processing Systems)
  10. ImageNet: A large-scale hierarchical image database

Their papers