?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. However, periodic behaviors could b...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays, P...
Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper present...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We provide a polynomial-time algorithm for this proble...
Adam Tauman Kalai, Ankur Moitra, and Gregory Valia...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...