It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
Most studies modeling inaccurate data in Gold style learning consider cases in which the number of inaccuracies is finite. The present paper argues that this approach is not reaso...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as ...
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...