Martin Slawski

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George Mason University

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Estimation in exponential family Regression based on linked data contaminated by mismatch error

Identification of matching records in multiple files can be a challengin...
10/01/2020 ∙ by Zhenbang Wang, et al. ∙ 0 ∙ share

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A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data

Recently, there has been significant interest in linear regression in th...
10/03/2019 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing

In "Unlabeled Sensing", one observes a set of linear measurements of an ...
09/05/2019 ∙ by Hang Zhang, et al. ∙ 1 ∙ share

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A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data

A tacit assumption in linear regression is that (response, predictor)-pa...
07/16/2019 ∙ by Martin Slawski, et al. ∙ 1 ∙ share

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A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression

Categorical regressor variables are usually handled by introducing a set...
05/17/2018 ∙ by Felicitas J. Detmer, et al. ∙ 0 ∙ share

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Linear Regression with Sparsely Permuted Data

In regression analysis of multivariate data, it is tacitly assumed that ...
10/16/2017 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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On Principal Components Regression, Random Projections, and Column Subsampling

Principal Components Regression (PCR) is a traditional tool for dimensio...
09/23/2017 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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Regularization-free estimation in trace regression with symmetric positive semidefinite matrices

Over the past few years, trace regression models have received considera...
04/23/2015 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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Estimation of positive definite M-matrices and structure learning for attractive Gaussian Markov Random fields

Consider a random vector with finite second moments. If its precision ma...
04/26/2014 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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Matrix factorization with Binary Components

Motivated by an application in computational biology, we consider low-ra...
01/23/2014 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization

Least squares fitting is in general not useful for high-dimensional line...
05/04/2012 ∙ by Martin Slawski, et al. ∙ 0 ∙ share

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