Oriana X. Wen

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—In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART classifiers to optimize both their classification error and their structural complexity. Towards this end, it combines the use of interacting sub-populations, some traditional(More)
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