Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
In this paper we address a method of source separation in the case where sources have certain temporal structures. The key contribution in this paper is to incorporate Gaussian pro...
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...