We consider the problem of sampling from constrained distributions, which has posed significant challenges to both non-asymptotic analysis and algorithmic design. We propose a unified framework, which is inspired by the classical mirror descent, to derive ...
Alcohol use is one of the world's leading causes of death and disease, although only a small proportion of individuals develop persistent alcohol use disorder (AUD). The identification of vulnerable individuals prior to their chronic intoxication remains o ...
Liouville copulas introduced in McNeil and Ne lehova (2010) are asymmetric generalizations of the ubiquitous Archimedean copula class. They are the dependence structures of scale mixtures of Dirichlet distributions, also called Liouville distributions. In ...
Background & Aims: Mitochondria) dysfunction, oxidative stress, inflammation, and metabolic reprograming are crucial contributors to hepatic injury and subsequent liver fibrosis. Poly(ADP-ribose) polymerases (PARP) and their interactions with sirtuins play ...
Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...
While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...
