Alexander Barg

Artificial Intelligence · 2005–2017

A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Alexander Barg trusts overall

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

  1. John C. Duchi
  2. Cynthia Dwork
  3. Peter Kairouz
  4. Martin J. Wainwright
  5. Min Ye
  6. Eric R. Ziegel
  7. Bin Yu
  8. Alexandre B. Tsybakov
  9. Michael I. Jordan
  10. Lucien Le Cam

Who trusts Alexander Barg overall

  1. Jayadev Acharya
  2. Min Ye
  3. J. F. I. Daniel J. Costello
  4. Xiao-Yu Hu
  5. Wei-Ning Chen
  6. Reza Olfati-Saber
  7. Vitaly Feldman
  8. Tianhao Wang
  9. Leighton Pate Barnes
  10. Ziteng Sun

Papers from Alexander Barg's perspective

Ordered by how strongly the researchers Alexander Barg 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. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Learning Multiple Layers of Features from Tiny Images
  7. Long Short-Term Memory
  8. Calibrating Noise to Sensitivity in Private Data Analysis
  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