Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
As a culture, object-orientation encourages programmers to create objects, both short- and long-lived, without concern for cost. Excessive object creation and initialization can ca...
In this paper we consider the problem of answering queries using views, with or without ontological constraints, which is important for data integration, query optimization, and d...
Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implemen...
Shashank Pandit, Duen Horng Chau, Samuel Wang, Chr...