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10/25/2022
Interpolating Discriminant Functions in High-Dimensional Gaussian Latent Mixtures
This paper considers binary classification of high-dimensional features ...
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10/23/2022
Optimal Discriminant Analysis in High-Dimensional Latent Factor Models
In high-dimensional classification problems, a commonly used approach is...
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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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01/20/2022
Inference in High-dimensional Multivariate Response Regression with Hidden Variables
This paper studies the inference of the regression coefficient matrix un...
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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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06/14/2021
Unique sparse decomposition of low rank matrices
The problem of finding the unique low dimensional decomposition of a giv...
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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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03/30/2020
Adaptive Estimation of Multivariate Regression with Hidden Variables
This paper studies the estimation of the coefficient matrix in multivar...
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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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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