Many large-scale Web applications that require ranked top-k retrieval are implemented using inverted indices. An inverted index represents a sparse term-document matrix, where non...
George Beskales, Marcus Fontoura, Maxim Gurevich, ...
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...