A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification ...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
—Conserving network-wide energy consumption is becoming an increasingly important concern for network operators. In this work, we study network-wide energy conservation problem w...
We investigate the problem of matching buyers and sellers in a multi-item multi-unit combinatorial exchange so as to maximize either the surplus (revenue minus cost) or the tradin...