Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Background: Innumerable biological investigations require comparing collections of molecules, cells or organisms to one another with respect to one or more of their properties. Al...
Modern trading and cluster applications require microsecond latencies and almost no losses in data centers. This paper introduces an algorithm called FineComb that can estimate ï¬...
Nearest Neighbor search is an important and widely used problem in a number of important application domains. In many of these domains, the dimensionality of the data representati...