Hai S. Le

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hai S. Le trusts overall

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

  1. Martin H. Anthony
  2. Luc Devroye
  3. Peter L. Bartlett
  4. Corinna Cortes
  5. Gary M. Weiss

Papers from Hai S. Le's perspective

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

  1. A Probabilistic Theory of Pattern Recognition
  2. Neural Network Learning: Theoretical Foundations
  3. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction (Journal of Artificial Intelligence Research)
  4. A general lower bound on the number of examples needed for learning
  5. AUC Optimization vs. Error Rate Minimization
  6. Applying Support Vector Machines to Imbalanced Datasets (European Conference on Machine Learning)
  7. The Nature of Statistical Learning Theory
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. A theory of the learnable
  10. ImageNet classification with deep convolutional neural networks

Their papers