Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Schema matching is the task of matching between concepts describing the meaning of data in various heterogeneous, distributed data sources. With many heuristics to choose from, sev...
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
Universally achievable error exponents pertaining to certain families of channels (most notably, discrete memoryless channels (DMC’s)), and various ensembles of random codes, ar...