J
Jerome H. Friedman
Researcher at Stanford University
Publications - 158
Citations - 156262
Jerome H. Friedman is an academic researcher from Stanford University. The author has contributed to research in topics: Lasso (statistics) & Multivariate statistics. The author has an hindex of 70, co-authored 155 publications receiving 138619 citations. Previous affiliations of Jerome H. Friedman include University of Washington.
Papers
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Journal ArticleDOI
Estimating Optimal Transformations for Multiple Regression and Correlation.
Leo Breiman,Jerome H. Friedman +1 more
TL;DR: In this article, a procedure for estimating functions θ and O 1, O 1, O p that minimize e 2 = E{[θ(Y) − Σ O j (Xj )]2}/var[ θ(X)], given only a sample {(yk, xk1, k 1, xkp ), 1 ⊽ k ⩽ N} and making minimal assumptions concerning the data distribution or the solution functions.
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A Projection Pursuit Algorithm for Exploratory Data Analysis
Jerome H. Friedman,John W. Tukey +1 more
TL;DR: An algorithm for the analysis of multivariate data is presented and is discussed in terms of specific examples to find one-and two-dimensional linear projections of multivariable data that are relatively highly revealing.
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Pathwise coordinate optimization
TL;DR: In this paper, coordinate-wise descent is used to solve the L1-penalized regression problem in the fused lasso problem, which is a non-separable problem in which coordinate descent does not work.
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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent
TL;DR: This work introduces a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ1 andℓ2 penalties (elastic net), and employs warm starts to find a solution along a regularization path.
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A Sparse-Group Lasso
TL;DR: A regularized model for linear regression with ℓ1 andℓ2 penalties is introduced and it is shown that it has the desired effect of group-wise and within group sparsity.