Yan Largman

Representation & Self-Supervised Learning · 2009

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 84 researchers here, as inferred from the citation graph.

Subfields

Whom Yan Largman trusts overall

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

  1. Douglas A. Reynolds
  2. Honglak Lee
  3. Geoffrey E. Hinton

Who trusts Yan Largman overall

  1. Li Deng
  2. Yoshua Bengio
  3. Dimitri Palaz
  4. Dong Yu
  5. Geoffrey E. Hinton
  6. Quoc V. Le
  7. Ossama Abdel-Hamid
  8. Sander Dieleman
  9. Aaron C. Courville
  10. Martin Längkvist

Papers from Yan Largman's perspective

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

  1. A Fast Learning Algorithm for Deep Belief Nets
  2. Training Products of Experts by Minimizing Contrastive Divergence
  3. Greedy Layer-Wise Training of Deep Networks
  4. ImageNet classification with deep convolutional neural networks
  5. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
  6. Emergence of simple-cell receptive field properties by learning a sparse code for natural images
  7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  8. Gradient-based learning applied to document recognition
  9. Sparse deep belief net model for visual area V2
  10. Self-taught learning: transfer learning from unlabeled data

Their papers