Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long ...
Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing camp...
Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, ...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...