Jin Yu

Optimization & Training · with Schraudolph · 2005–2008

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

Whom Jin Yu trusts overall

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

  1. Thorsten Joachims
  2. Choon Hui Teo
  3. N. Schraudolph
  4. Vojtech Franc
  5. Jorge Nocedal
  6. Galen Andrew
  7. Sham M. Kakade
  8. Shun-ichi Amari
  9. Martin Fodslette Møller
  10. Kevin P. Murphy

Who trusts Jin Yu overall

  1. Aryan Mokhtari
  2. Adith Swaminathan
  3. Farbod Roosta-Khorasani
  4. Wei Xu
  5. Frank E. Curtis
  6. Thorsten Joachims
  7. Mark Eisen
  8. Michael W. Mahoney
  9. Alejandro Ribeiro
  10. Virginia Smith

Papers from Jin Yu's perspective

Ordered by how strongly the researchers Jin Yu 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers