research
∙
12/30/2022
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach
Statistical inference on the cancer-site specificities of collective ult...
share
research
∙
06/22/2022
Bregman Power k-Means for Clustering Exponential Family Data
Recent progress in center-based clustering algorithms combats poor local...
research
∙
01/06/2022
Robust Linear Predictions: Analyses of Uniform Concentration, Fast Rates and Model Misspecification
The problem of linear predictions has been extensively studied for the p...
research
∙
12/20/2021
Convergence properties of data augmentation algorithms for high-dimensional robit regression
The logistic and probit link functions are the most common choices for r...
research
∙
10/27/2021
Uniform Concentration Bounds toward a Unified Framework for Robust Clustering
Recent advances in center-based clustering continue to improve upon the ...
research
∙
05/01/2021
t-Entropy: A New Measure of Uncertainty with Some Applications
The concept of Entropy plays a key role in Information Theory, Statistic...
research
∙
02/05/2021
Robust Principal Component Analysis: A Median of Means Approach
Principal Component Analysis (PCA) is a fundamental tool for data visual...
research
∙
12/20/2020
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm
Mean shift is a simple interactive procedure that gradually shifts data ...
research
∙
11/12/2020
Kernel k-Means, By All Means: Algorithms and Strong Consistency
Kernel k-means clustering is a powerful tool for unsupervised learning o...
research
∙
08/17/2020
Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction clustering
Even with the rise in popularity of over-parameterized models, simple di...
research
∙
08/04/2020
Biconvex Clustering
Convex clustering has recently garnered increasing interest due to its a...
research
∙
05/21/2020
Using the "Hidden" Genome to Improve Classification of Cancer Types
It is increasingly common clinically for cancer specimens to be examined...
research
∙
01/10/2020
Entropy Regularized Power k-Means Clustering
Despite its well-known shortcomings, k-means remains one of the most wid...
research
∙
11/03/2019
Estimating accuracy of the MCMC variance estimator: a central limit theorem for batch means estimators
The batch means estimator of the MCMC variance is a simple and effective...
research
∙
03/24/2019
A Strongly Consistent Sparse k-means Clustering with Direct l_1 Penalization on Variable Weights
We propose the Lasso Weighted k-means (LW-k-means) algorithm as a simple...
research
∙
04/23/2018
On the circular correlation coefficients for bivariate von Mises distributions on a torus
This paper studies circular correlations for the bivariate von Mises sin...
research
∙
11/02/2017
Consistent estimation of the spectrum of trace class data augmentation algorithms
Markov chain Monte Carlo is widely used in a variety of scientific appli...
research
∙
08/25/2017
BAMBI: An R package for Fitting Bivariate Angular Mixture Models
Statistical analyses of directional or angular data have applications in...
research
∙
05/09/2014