Patrick Breheny

Statistics and Probability · 2011–2018

A researcher in the Science corpus: 6 papers; trusts 54 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 92 citations into it; #1,127 of 12,932 by trust here, #3,255 by citations
• Artificial Intelligence — 33 citations into it; #4,793 of 35,345 by trust here, #18,186 by citations
• Computational Mechanics — 29 citations into it; #833 of 10,001 by trust here, #3,908 by citations
• Optimization & Training — 19 citations into it
• Statistical Learning Theory — 14 citations into it
• Control and Systems Engineering — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it; #15,592 of 21,575 by trust here, #21,424 by citations
• Mathematical Optimization — 8 citations into it

Whom Patrick Breheny trusts overall

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

1. Jerome H. Friedman
2. Robert Tibshirani
3. Trevor J. Hastie
4. Hui Zou
5. Cun-Hui Zhang
6. Leo Breiman
7. Kenneth L. Lange
8. Jian Huang
9. Jianqing Fan
10. Paul Tseng

Who trusts Patrick Breheny overall

1. Tomohiro Ando
2. Jian Huang
3. Ryan A. Peterson
4. Cun-Hui Zhang
5. Yingying Fan
6. Po-Ling Loh
7. Bo Peng
8. Xueying Chen
9. Ker-Chau Li
10. Veronika Rocková

Papers from Patrick Breheny's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Model selection and estimation in regression with grouped variables
3. Atomic Decomposition by Basis Pursuit
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. High-dimensional graphs and variable selection with the Lasso
9. Addendum: Regularization and variable selection via the elastic net
10. PATHWISE COORDINATE OPTIMIZATION

Their papers

• COORDINATE DESCENT ALGORITHMS FOR NONCONVEX PENALIZED REGRESSION, WITH APPLICATIONS TO BIOLOGICAL FEATURE SELECTION (2011) — 823 citations
• A Selective Review of Group Selection in High-Dimensional Models. (2012) — 407 citations
• Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors (2012) — 324 citations
• Visualization of Regression Models Using visreg (2017) — 928 citations
• The Jackknife (2018)
• THE Mnet method for variable selection (2016) — 65 citations