We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
We give a precise definition of "generic-case complexity" and show that for a very large class of finitely generated groups the classical decision problems of group theor...
Ilya Kapovich, Alexei G. Myasnikov, Paul Schupp, V...
Background: Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image unders...
Raffaele Di Natale, Alfredo Ferro, Rosalba Giugno,...
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing pl...
Yingyi Bu, Bill Howe, Magdalena Balazinska, Michae...
Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a ...nite dimensional space. The results imply ...