Shuheng Zhou | DeepAI

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John Lafferty
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∙ 04/02/2023

Sharp rates of convergence for the tensor graphical Lasso estimator

Building models and methods for complex data is an important task for ma...

0 Kristjan Greenewald, et al. ∙

∙ 01/01/2023

Semidefinite programming on population clustering: a global analysis

In this paper, we consider the problem of partitioning a small data samp...

0 Shuheng Zhou, et al. ∙

∙ 08/07/2020

The Tensor Quadratic Forms

We consider the following data perturbation model, where the covariates ...

0 Shuheng Zhou, et al. ∙

∙ 04/07/2019

Precision Matrix Estimation with Noisy and Missing Data

Estimating conditional dependence graphs and precision matrices are some...

0 Roger Fan, et al. ∙

∙ 08/15/2018

Tensor models for linguistics pitch curve data of native speakers of Afrikaans

We use tensor analysis techniques for high-dimensional data to gain insi...

0 Michael Hornstein, et al. ∙

∙ 11/10/2017

Time-dependent spatially varying graphical models, with application to brain fMRI data analysis

In this work, we present an additive model for space-time data that spli...

0 Kristjan Greenewald, et al. ∙

∙ 11/15/2016

Errors-in-variables models with dependent measurements

Suppose that we observe y ∈R^n and X ∈R^n × m in the following errors-in...

0 Mark Rudelson, et al. ∙

∙ 11/13/2016

Joint mean and covariance estimation with unreplicated matrix-variate data

It has been proposed that complex populations, such as those that arise ...

0 Michael Hornstein, et al. ∙

∙ 02/09/2015

High dimensional errors-in-variables models with dependent measurements

Suppose that we observe y ∈R^f and X ∈R^f × m in the following errors-in...

0 Mark Rudelson, et al. ∙

∙ 09/23/2012

Gemini: Graph estimation with matrix variate normal instances

Undirected graphs can be used to describe matrix variate distributions. ...

0 Shuheng Zhou, et al. ∙

∙ 04/03/2012

Convergence Properties of Kronecker Graphical Lasso Algorithms

This paper studies iteration convergence of Kronecker graphical lasso (K...

0 Theodoros Tsiligkaridis, et al. ∙

∙ 09/02/2010

High-dimensional covariance estimation based on Gaussian graphical models

Undirected graphs are often used to describe high dimensional distributi...

0 Shuheng Zhou, et al. ∙

∙ 12/21/2009

Restricted Eigenvalue Conditions on Subgaussian Random Matrices

It is natural to ask: what kinds of matrices satisfy the Restricted Eige...

0 Shuheng Zhou, et al. ∙

∙ 02/20/2008

Time Varying Undirected Graphs

Undirected graphs are often used to describe high dimensional distributi...

0 Shuheng Zhou, et al. ∙

∙ 02/10/2008

Learning Balanced Mixtures of Discrete Distributions with Small Sample

We study the problem of partitioning a small sample of n individuals fro...

0 Shuheng Zhou, et al. ∙

∙ 06/25/2007

Separating populations with wide data: A spectral analysis

In this paper, we consider the problem of partitioning a small data samp...

0 Avrim Blum, et al. ∙

∙ 06/04/2007

Compressed Regression

Recent research has studied the role of sparsity in high dimensional reg...

0 Shuheng Zhou, et al. ∙