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02/23/2023
Asymptotic confidence sets for random linear programs
Motivated by the statistical analysis of the discrete optimal transport ...
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06/26/2022
The Sketched Wasserstein Distance for mixture distributions
The Sketched Wasserstein Distance (W^S) is a new probability distance sp...
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07/12/2021
Likelihood estimation of sparse topic distributions in topic models and its applications to Wasserstein document distance calculations
This paper studies the estimation of high-dimensional, discrete, possibl...
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10/05/2020
Detecting approximate replicate components of a high-dimensional random vector with latent structure
High-dimensional feature vectors are likely to contain sets of measureme...
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07/20/2020
Prediction in latent factor regression: Adaptive PCR and beyond
This work is devoted to the finite sample prediction risk analysis of a ...
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02/06/2020
Interpolation under latent factor regression models
This work studies finite-sample properties of the risk of the minimum-no...
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01/22/2020
Optimal estimation of sparse topic models
Topic models have become popular tools for dimension reduction and explo...
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05/29/2019
Essential regression
Essential Regression is a new type of latent factor regression model, wh...
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06/13/2018
High-Dimensional Inference for Cluster-Based Graphical Models
Motivated by modern applications in which one constructs graphical model...
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05/17/2018
A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics
We propose a new method of estimation in topic models, that is not a var...
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04/23/2017
Sparse Latent Factor Models with Pure Variables for Overlapping Clustering
The problem of overlapping variable clustering, ubiquitous in data scien...
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08/08/2015
Minimax Optimal Variable Clustering in G-Block Correlation Models via Cord
The goal of variable clustering is to partition a random vector X∈ R^p ...
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05/23/2014
Convex Banding of the Covariance Matrix
We introduce a new sparse estimator of the covariance matrix for high-di...
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10/17/2011