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. ...
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
A query considered in isolation offers limited information about a searcher's intent. Query context that considers pre-query activity (e.g., previous queries and page visits)...
We describe the design and evaluation of two different dynamic student uncertainty adaptations in wizarded versions of a spoken dialogue tutoring system. The two adaptive systems...
A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...