Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Annalisa Appice,Pedro Pereira Rodrigues,Carlos Soa Conference p

尖酸一點(diǎn)

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 clas

MERIT

AVANT

Ingrained

珍奇

Canyon

Osteoporosis

languor

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