We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Many computation-intensive or recursive applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). ...
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 ...
We combine the work of Garg and K¨onemann, and Fleischer with ideas from dynamic graph algorithms to obtain faster (1 − ε)-approximation schemes for various versions of the mu...
The "nearest neighbor" relation, or more generally the "k nearest neighbors" relation, defined for a set of points in a metric space, has found many uses in co...