Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...