Jonathan Terhorst

Optimization & Training · 2014–2016

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

Whom Jonathan Terhorst trusts overall

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

  1. Richard Durbin
  2. Heng Li
  3. Stephan Schiffels
  4. Laurent Excoffier
  5. Peter Richtárik
  6. Shai Shalev-Shwartz
  7. Tianbao Yang
  8. Martin Takác
  9. Ryan N. Gutenkunst
  10. L. Eon Bottou

Who trusts Jonathan Terhorst overall

  1. Jakub Konecný
  2. Virginia Smith
  3. Chenxin Ma
  4. Jason D. Lee
  5. Martin Takác
  6. Peter Richtárik

Papers from Jonathan Terhorst's perspective

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

  1. A Stochastic Approximation Method
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Pegasos: primal estimated sub-gradient solver for SVM
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  8. Parallelized Stochastic Gradient Descent
  9. Learning Multiple Layers of Features from Tiny Images
  10. Stochastic dual coordinate ascent methods for regularized loss

Their papers