Nicholas Kissel

Statistics and Probability · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nicholas Kissel trusts overall

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

  1. Trevor J. Hastie
  2. Robert Tibshirani
  3. Leo Breiman
  4. E.J. Candes
  5. Theja Tulabandhula
  6. Cynthia Rudin
  7. Jonathan E. Taylor
  8. Tong Zhang
  9. Francis R. Bach
  10. Rina Foygel Barber

Papers from Nicholas Kissel's perspective

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

  1. Regression Shrinkage and Selection via the Lasso
  2. 双対平坦空間におけるLeast Angle Regressionと情報量規準
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. The Nature of Statistical Learning Theory
  6. Gradient-based learning applied to document recognition
  7. On Model Selection Consistency of Lasso
  8. Model selection and estimation in regression with grouped variables
  9. Estimating the Dimension of a Model
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers