Ying Cao

Artificial Intelligence · with Gao · 2013

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ying Cao trusts overall

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

  1. Eric R. Ziegel
  2. Robert E. Schapire
  3. Jerome H. Friedman
  4. Yoav Freund
  5. Leo Breiman

Papers from Ying Cao's perspective

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

  1. The Elements of Statistical Learning
  2. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. The Nature of Statistical Learning Theory
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Going deeper with convolutions
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Regression Shrinkage and Selection via the Lasso
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers