
Estimation in exponential family Regression based on linked data contaminated by mismatch error
Identification of matching records in multiple files can be a challengin...
read it

A PseudoLikelihood Approach to Linear Regression with Partially Shuffled Data
Recently, there has been significant interest in linear regression in th...
read it

Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing
In "Unlabeled Sensing", one observes a set of linear measurements of an ...
read it

A TwoStage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
A tacit assumption in linear regression is that (response, predictor)pa...
read it

A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression
Categorical regressor variables are usually handled by introducing a set...
read it

Linear Regression with Sparsely Permuted Data
In regression analysis of multivariate data, it is tacitly assumed that ...
read it

On Principal Components Regression, Random Projections, and Column Subsampling
Principal Components Regression (PCR) is a traditional tool for dimensio...
read it

Regularizationfree estimation in trace regression with symmetric positive semidefinite matrices
Over the past few years, trace regression models have received considera...
read it

Estimation of positive definite Mmatrices and structure learning for attractive Gaussian Markov Random fields
Consider a random vector with finite second moments. If its precision ma...
read it

Matrix factorization with Binary Components
Motivated by an application in computational biology, we consider lowra...
read it

Nonnegative least squares for highdimensional linear models: consistency and sparse recovery without regularization
Least squares fitting is in general not useful for highdimensional line...
read it
Martin Slawski
is this you? claim profile