Findings from Changsha University of Science and Technology Provides New Data ab out Support Vector Machines (Sparse and Robust Support Vector Machine With Capped Squared Loss for Largescale Pattern Classification)

Robotics & Machine Learning Daily News2024，Issue(Sep.3) ：126-126.

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Findings from Changsha University of Science and Technology Provides New Data ab out Support Vector Machines (Sparse and Robust Support Vector Machine With Capped Squared Loss for Largescale Pattern Classification)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Su pport Vector Machines. According to newsreporting from Changsha, People’s Repub lic of China, by NewsRx journalists, research stated, “Supportvector machine (S VM), being considered one of the most efficient tools for classification, has re ceivedwidespread attention in various fields. However, its performance is hinde red when dealing with large-scalepattern classification tasks due to high memor y requirements and running very slow.”

Key words

Changsha/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Support Vector Machines/Vector Mac hines/Changsha University of Science and Technology

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出版年

2024

Robotics & Machine Learning Daily News

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