Providing up-to-date input to users’ applications is an important data management problem for a distributed computing environment, where each data storage location and intermedi...
Mitchell D. Theys, Noah Beck, Howard Jay Siegel, M...
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
The augmented graph model, as introduced by Kleinberg (STOC 2000), is an appealing model for analyzing navigability in social networks. Informally, this model is defined by a pair...
This paper presents a middleware framework for storing, accessing and analyzing massive-scale semantic graphs. The framework, MSSG, targets scale-free semantic graphs with O(1012 ...
We give new algorithms for learning halfspaces in the challenging malicious noise model, where an adversary may corrupt both the labels and the underlying distribution of examples....
Adam R. Klivans, Philip M. Long, Rocco A. Servedio