Dan Garber

Optimization & Training · 2009–2017

A researcher in the Science corpus: 6 papers; trusts 40 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

Whom Dan Garber trusts overall

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

  1. Martin Jaggi
  2. Kenneth L. Clarkson
  3. Yurii E. Nesterov
  4. Simon Lacoste-Julien
  5. Guanghui Lan
  6. Shai Shalev-Shwartz
  7. Alexander Schrijver
  8. Amir Beck
  9. Martin A. Zinkevich
  10. Philip Wolfe

Who trusts Dan Garber overall

  1. Zeyuan Allen-Zhu
  2. Sebastian Pokutta
  3. Thomas Kerdreux
  4. Gábor Braun
  5. Cyrille W. Combettes
  6. Simon Lacoste-Julien
  7. Frédéric Koriche
  8. Marco S. Molinaro
  9. Gauthier Gidel
  10. Yi Xu

Papers from Dan Garber's perspective

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

Their papers