Alexander M. Malyscheff

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Support vector machines have recently attracted much attention in the machine learning and optimization communities for their remarkable generalization ability. The support vector machine solution corresponds to the center of the largest hypersphere inscribed in the version space. Recently, however, alternative approaches [4] have suggested that the(More)
in Taiwan. He worked as a production control engineer before joining Purdue. His research interests include student success models, team effectiveness, neural network, fuzzy computing, data mining and production systems. he worked as a Risk Analyst in Energy Trading. His research interests include modeling of student data, team effectiveness, mathematical(More)
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