In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
Abstract-- Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, outdated sources and sampling errors. Thes...
In many applications, classifiers need to be built based on multiple related data streams. For example, stock streams and news streams are related, where the classification patter...
Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Rong She, Jian ...
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...