A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
Finding a proper distribution of translation probabilities is one of the most important factors impacting the effectiveness of a crosslanguage information retrieval system. In th...
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...