Hui Han

Artificial Intelligence · Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004. · 2003–2005

A researcher in the Science corpus: 3 papers; trusts 23 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Hui Han trusts overall

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

  1. Hongyuan Zha
  2. Thorsten Joachims
  3. Vladimir Naumovich Vapni
  4. Dustin Boswell
  5. Robert Krovetz
  6. Jianbo Shi
  7. Satanjeev Banerjee
  8. Andrew Y. Ng
  9. Sheila Tejada
  10. Xiaofeng He

Who trusts Hui Han overall

  1. Vetle I. Torvik
  2. Neil R. Smalheiser
  3. Miriam J. Metzger
  4. Hongyuan Zha
  5. C. Lee Giles

Papers from Hui Han's perspective

Ordered by how strongly the researchers Hui Han 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. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers