Hua Ouyang

Optimization & Training · with Gray · 2010–2013

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Hua Ouyang trusts overall

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

  1. Yurii E. Nesterov
  2. Vladimir Naumovich Vapnik
  3. Kenneth L. Clarkson
  4. Guanghui Lan
  5. Junfeng Yang
  6. Vladimir Naumovich Vapni
  7. Lin Xiao
  8. Robert Tibshirani
  9. L. Eon Bottou
  10. Alex Smola

Who trusts Hua Ouyang overall

  1. Tianbao Yang
  2. Taiji Suzuki
  3. Martin Jaggi
  4. Jean Lafond
  5. Simon Lacoste-Julien
  6. Ricardo Ñanculef
  7. Samaneh Azadi
  8. Ruiliang Zhang
  9. Pascal Bianchi
  10. Huihui Wang

Papers from Hua Ouyang's perspective

Ordered by how strongly the researchers Hua Ouyang 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. ImageNet: A large-scale hierarchical image database
  7. Attention is All you Need (Neural Information Processing Systems)
  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