—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
Sparse regression is the problem of selecting a parsimonious subset of all available regressors for an efficient prediction of a target variable. We consider a general setting in w...
In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clus...
We consider a finite-state Markov decision problem and establish the convergence of a special case of optimistic policy iteration that involves Monte Carlo estimation of Q-values,...
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...