714 citations · 827 across the 5 of their papers we have counts for
5 papers
Fast-rate and optimistic-rate error bounds for L1-regularized regression
Rina Foygel, Nathan Srebro
We consider the prediction error of linear regression with L1 regularization when the number of covariates p is large relative to the sample size n. When the model is k-sparse and…
Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions
Rina Foygel, Ruslan Salakhutdinov, Ohad Shamir +1
We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions. We show that the standard weighted trace-norm might fail when the sa…
Concentration-Based Guarantees for Low-Rank Matrix Reconstruction
Rina Foygel, Nathan Srebro
We consider the problem of approximately reconstructing a partially-observed, approximately low-rank matrix. This problem has received much attention lately, mostly using the trace…
Extended Bayesian Information Criteria for Gaussian Graphical Models
Rina Foygel, Mathias Drton
Gaussian graphical models with sparsity in the inverse covariance matrix are of significant interest in many modern applications. For the problem of recovering the graphical struct…
Exact block-wise optimization in group lasso and sparse group lasso for linear regression
Rina Foygel, Mathias Drton
The group lasso is a penalized regression method, used in regression problems where the covariates are partitioned into groups to promote sparsity at the group level. Existing meth…