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Sep 12, 2018
Optimization and Control
Machine Learning

A Fast Globally Linearly Convergent Algorithm for the Computation of …

In this paper, we consider the problem of computing a Wasserstein barycenter for a set of discrete probability distributions with finite supports, wh…
Dec 04, 2013

Long-term Variability in the Length of the Solar Cycle

The recent paucity of sunspots and the delay in the expected start of Solar Cycle 24 have drawn attention to the challenges involved in predicting so…
Feb 03, 2013
Machine Learning
Computer Vision

Parallel D2-Clustering: Large-Scale Clustering of Discrete Distributi…

The discrete distribution clustering algorithm, namely D2-clustering, has demonstrated its usefulness in image classification and annotation where ea…
Jul 25, 2011
Applications

Causal inference in transportation safety studies: Comparison of po…

The research questions that motivate transportation safety studies are causal in nature. Safety researchers typically use observational data to answe…
Apr 20, 2015
Statistics Theory

Theoretical Grounding for Estimation in Conditional Independence Mu…

For the nonparametric estimation of multivariate finite mixture models with the conditional independence assumption, we propose a new formulation of …
Sep 12, 2018
Optimization and Control
Machine Learning

A Fast Globally Linearly Convergent Algorithm for the Computation of …

In this paper, we consider the problem of computing a Wasserstein barycenter for a set of discrete probability distributions with finite supports, wh…
Mar 21, 2014
Statistics Theory

On efficient dimension reduction with respect to a statistical func…

We introduce a new sufficient dimension reduction framework that targets a statistical functional of interest, and propose an efficient estimator for…
Oct 09, 2012
Statistics Theory
Probability

The affinely invariant distance correlation

Sz\'{e}kely, Rizzo and Bakirov (Ann. Statist. 35 (2007) 2769-2794) and Sz\'{e}kely and Rizzo (Ann. Appl. Statist. 3 (2009) 1236-1265), in two seminal…
Mar 06, 2013
Applications
Methodology

Fast dimension-reduced climate model calibration and the effect of da…

How will the climate system respond to anthropogenic forcings? One approach to this question relies on climate model projections. Current climate pro…
Nov 25, 2011
Applications

Block-based Bayesian epistasis association mapping with application t…

Interactions among multiple genes across the genome may contribute to the risks of many complex human diseases. Whole-genome single nucleotide polymo…
May 02, 2012
Computation

Markov chain Monte Carlo (MCMC) algorithms provide a very general recipe for estimating properties of complicated distributions. While their use has become commonplace and there is a large literature on MCMC theory and practice, MCMC users still hav…

On automating Markov chain Monte Carlo for a class of spatial models

Markov chain Monte Carlo (MCMC) algorithms provide a very general recipe for estimating properties of complicated distributions. While their use has …
Jul 04, 2014
Statistics Theory

Asymptotics of nonparametric L-1 regression models with dependent data

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric re…
Feb 02, 2016
Statistics Theory

Independent component analysis for tensor-valued data

In preprocessing tensor-valued data, e.g. images and videos, a common procedure is to vectorize the observations and subject the resulting vectors to…
May 31, 2011
Other Statistics
Discrete Mathematics
Statistics Theory

Maximum lilkelihood estimation in the $β$-model

We study maximum likelihood estimation for the statistical model for undirected random graphs, known as the $\beta$-model, in which the degree sequen…
Nov 02, 2012
Statistics Theory

Variable selection in linear mixed effects models

This paper is concerned with the selection and estimation of fixed and random effects in linear mixed effects models. We propose a class of nonconcav…
Feb 05, 2015
Statistics Theory

Distance Correlation Coefficients for Lancaster Distributions

We consider the problem of calculating distance correlation coefficients between random vectors whose joint distributions belong to the class of Lanc…
Feb 01, 2013
Statistics Theory

Inference for modulated stationary processes

We study statistical inferences for a class of modulated stationary processes with time-dependent variances. Due to non-stationarity and the large nu…
Feb 18, 2013
Statistics Theory

Multivariate varying coefficient model for functional responses

Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for …
Aug 26, 2015
Machine Learning

Gaussian Mixture Models with Component Means Constrained in Pre-selec…

We investigate a Gaussian mixture model (GMM) with component means constrained in a pre-selected subspace. Applications to classification and cluster…
Aug 24, 2014
Statistics Theory

Maximum Likelihood Estimation for Linear Gaussian Covariance Models

We study parameter estimation in linear Gaussian covariance models, which are $p$-dimensional Gaussian models with linear constraints on the covarian…
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