We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
Resource allocation is a key problem in autonomic computing. In this paper we use a data center scenario to motivate the need for decentralization and cooperative negotiation, and...
Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart,...
In this work we design algorithms for clustering relational columns into attributes, i.e., for identifying strong relationships between columns based on the common properties and ...
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we conside...