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06/01/2023
A General Framework for Regression with Mismatched Data Based on Mixture Modeling
Data sets obtained from linking multiple files are frequently affected b...
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03/09/2022
Reevaluating COVID-19 Mandates using Tensor Completion
We propose a new method that uses tensor completion to estimate causal e...
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01/10/2022
Permuted and Unlinked Monotone Regression in ℝ^d: an approach based on mixture modeling and optimal transport
Suppose that we have a regression problem with response variable Y in ℝ^...
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11/02/2021
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
In the analysis of data sets consisting of (X, Y)-pairs, a tacit assumpt...
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10/01/2020
Estimation in exponential family Regression based on linked data contaminated by mismatch error
Identification of matching records in multiple files can be a challengin...
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10/03/2019
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data
Recently, there has been significant interest in linear regression in th...
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09/05/2019
Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing
In "Unlabeled Sensing", one observes a set of linear measurements of an ...
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07/16/2019
A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
A tacit assumption in linear regression is that (response, predictor)-pa...
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05/17/2018
A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression
Categorical regressor variables are usually handled by introducing a set...
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10/16/2017
Linear Regression with Sparsely Permuted Data
In regression analysis of multivariate data, it is tacitly assumed that ...
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09/23/2017
On Principal Components Regression, Random Projections, and Column Subsampling
Principal Components Regression (PCR) is a traditional tool for dimensio...
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04/23/2015
Regularization-free estimation in trace regression with symmetric positive semidefinite matrices
Over the past few years, trace regression models have received considera...
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04/26/2014
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...
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01/23/2014
Matrix factorization with Binary Components
Motivated by an application in computational biology, we consider low-ra...
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05/04/2012