Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
Recommendations are crucial for the success of large websites. While there are many ways to determine recommendations, the relative quality of these recommenders depends on many fa...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
We address the issue of providing highly informative and comprehensive annotations using information revealed by the structured vocabularies of Gene Ontology (GO). For a target, a...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...