6 papers
Sparse Separable Factor Analysis in the Complex Domain with an Application to Local Field Potential Data
Ian Hultman, Kirtikanth Kalapatapu, Yassine Filali +2
Complex-valued arrays arise in signal processing, where scientific interpretation depends on retaining amplitude and phase information. Existing covariance estimation methods eithe…
Moment bounds for condition numbers and singular values of high-dimensional Gaussian random matrices: Applications and limitations
Partha Sarkar, Kshitij Khare, Sanvesh Srivastava
Spectral properties of Gram matrices are central to high dimensional asymptotic analyses of statistical estimators in regression and covariance estimation. These properties, in tur…
CoMET: A Compressed Bayesian Mixed-Effects Model for High-Dimensional Tensors
Sreya Sarkar, Kshitij Khare, Sanvesh Srivastava
Mixed-effects models are fundamental tools for analyzing clustered and repeated-measures data, but existing high-dimensional methods largely focus on penalized estimation with vect…
Asynchronous Distributed ECME Algorithm for Matrix Variate Non-Gaussian Responses
Qingyang Liu, Sanvesh Srivastava, Dipankar Bandyopadhyay
We propose a regression model with matrix-variate skew-t response (REGMVST) for analyzing irregular longitudinal data with skewness, symmetry, or heavy tails. REGMVST models matrix…
SLIM-LLMs: Modeling of Style-Sensory Language RelationshipsThrough Low-Dimensional Representations
Osama Khalid, Sanvesh Srivastava, Padmini Srinivasan
Sensorial language -- the language connected to our senses including vision, sound, touch, taste, smell, and interoception, plays a fundamental role in how we communicate experienc…
Regularized Parameter Estimation in Mixed Model Trace Regression
Ian Hultman, Sanvesh Srivastava
We introduce mixed model trace regression (MMTR), a mixed model linear regression extension for scalar responses and high-dimensional matrix-valued covariates. MMTR's fixed effects…