Ouyi Li

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ouyi Li trusts

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

  1. Jorge Nocedal (in Optimization & Training)
  2. James Martens (in Optimization & Training)
  3. Timothy Dozat (in Optimization & Training)
  4. Boris Polyak (in Numerical Methods & Scientific Computing)

Papers from Ouyi Li's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. Gradient-based learning applied to document recognition
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  5. Rectified Linear Units Improve Restricted Boltzmann Machines
  6. On the importance of initialization and momentum in deep learning
  7. ImageNet classification with deep convolutional neural networks
  8. Deep learning via Hessian-free optimization
  9. Natural Language Processing (Almost) from Scratch
  10. Learning Multiple Layers of Features from Tiny Images

Their papers