A Semismooth-Newton's-Method-Based Linearization and Approximation Approach for Kernel Support Vector Machines

21 Jul 2020 Chen Jiang Qingna Li

Support Vector Machines (SVMs) are among the most popular and the best performing classification algorithms. Various approaches have been proposed to reduce the high computation and memory cost when training and predicting based on large-scale datasets with kernel SVMs... (read more)

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