714 citations · 850 across the 7 of their papers we have counts for
7 papers
Nonparametric Reduced Rank Regression
Rina Foygel, Michael Horrell, Mathias Drton +1
We propose an approach to multivariate nonparametric regression that generalizes reduced rank regression for linear models. An additive model is estimated for each dimension of a $…
Matrix reconstruction with the local max norm
Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov
We introduce a new family of matrix norms, the "local max" norms, generalizing existing methods such as the max norm, the trace norm (nuclear norm), and the weighted or smoothed we…
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…