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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...
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01/01/2023
Semidefinite programming on population clustering: a global analysis
In this paper, we consider the problem of partitioning a small data samp...
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08/07/2020
The Tensor Quadratic Forms
We consider the following data perturbation model, where the covariates ...
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04/07/2019
Precision Matrix Estimation with Noisy and Missing Data
Estimating conditional dependence graphs and precision matrices are some...
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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...
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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...
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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...
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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 ...
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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...
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09/23/2012
Gemini: Graph estimation with matrix variate normal instances
Undirected graphs can be used to describe matrix variate distributions. ...
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04/03/2012
Convergence Properties of Kronecker Graphical Lasso Algorithms
This paper studies iteration convergence of Kronecker graphical lasso (K...
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09/02/2010
High-dimensional covariance estimation based on Gaussian graphical models
Undirected graphs are often used to describe high dimensional distributi...
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12/21/2009
Restricted Eigenvalue Conditions on Subgaussian Random Matrices
It is natural to ask: what kinds of matrices satisfy the Restricted Eige...
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02/20/2008
Time Varying Undirected Graphs
Undirected graphs are often used to describe high dimensional distributi...
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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...
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06/25/2007
Separating populations with wide data: A spectral analysis
In this paper, we consider the problem of partitioning a small data samp...
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06/04/2007
