New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...
Both itemset mining and graph mining have been studied independently. Here, we introduce a novel data structure, which is an unweighted graph whose vertices contain itemsets. From ...
Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun S...
—In addition to their role as simulation engines, modern supercomputers can be harnessed for scientific visualization. Their extensive concurrency, parallel storage systems, and...
Tom Peterka, Hongfeng Yu, Robert B. Ross, Kwan-Liu...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...