尖酸一点 发表于 2025-3-30 10:31:15
Multi-Task Learning with Group-Specific Feature Space Sharingzation performance. (MTL) exploits the latent relations between tasks and overcomes data scarcity limitations by co-learning all these tasks simultaneously to offer improved performance. We propose a novel Multi-Task Multiple Kernel Learning framework based on Support Vector Machines for binary clasMERIT 发表于 2025-3-30 15:36:58
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http://reply.papertrans.cn/63/6206/620502/620502_53.pngIngrained 发表于 2025-3-30 23:44:19
http://reply.papertrans.cn/63/6206/620502/620502_54.png珍奇 发表于 2025-3-31 04:22:06
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http://reply.papertrans.cn/63/6206/620502/620502_56.pngOsteoporosis 发表于 2025-3-31 12:14:25
http://reply.papertrans.cn/63/6206/620502/620502_57.pnglanguor 发表于 2025-3-31 15:25:49
Fast Training of Support Vector Machines for Survival Analysisdical research. When applied to large amounts of patient data, efficient optimization routines become a necessity. We propose efficient training algorithms for three kinds of linear survival support vector machines: 1) ranking-based, 2) regression-based, and 3) combined ranking and regression. We pe