Mark Herbster

Artificial Intelligence · 1995–2017

A researcher in the Science corpus: 4 papers; trusts 12 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

Whom Mark Herbster trusts overall

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

  1. Nick Littlestone
  2. Yoav Freund
  3. Manfred K. Warmuth
  4. Bernhard E. Boser
  5. Peter Auer
  6. Radford M. Neal
  7. Robert E. Schapire
  8. Geoffrey E. Hinton
  9. Yuhai Wu
  10. Edward Farhi

Who trusts Mark Herbster overall

  1. András György
  2. Eric C. Hall
  3. Nicolò Cesa-Bianchi
  4. Tor Lattimore
  5. Csaba Szepesvari
  6. Mehryar Mohri
  7. Gábor Lugosi
  8. Lijun Zhang
  9. Martin A. Zinkevich
  10. Rebecca M. Willett

Papers from Mark Herbster's perspective

Ordered by how strongly the researchers Mark Herbster 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. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Learning Multiple Layers of Features from Tiny Images
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. GENERATIVE ADVERSARIAL NETS
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers