Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management. Most existing data-mining alg...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
Abstract--This paper presents a dynamic predictiveoptimization framework of a nonlinear temporal process. Datamining (DM) and evolutionary strategy algorithms are integrated in the...
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...