Eric B. Baum

Statistical Learning Theory · 1988–1991

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Eric B. Baum trusts overall

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

  1. Thomas M. Cover
  2. Geoffrey E. Hinton
  3. Paul J. Werbos
  4. John J. Hopfield
  5. David E. Rumelhart
  6. Terrence J. Sejnowski
  7. David H. Ackley
  8. Yann LeCun
  9. David Haussler
  10. Arthur L. Samuel

Who trusts Eric B. Baum overall

  1. Robert E. Schapire
  2. Yoav Freund
  3. G. Huang
  4. Geoffrey E. Hinton
  5. Allan Pinkus
  6. Daniel Soudry
  7. Yoshua Bengio
  8. J. Urgen Schmidhuber
  9. David John Cameron MacKay
  10. Shun-ichi Amari

Papers from Eric B. Baum's perspective

Ordered by how strongly the researchers Eric B. Baum 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. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers