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Introduction to Graphical Models for Data Mining

Introduction to Graphical Models for Data Mining

This video was recorded at 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington 2010. Graphical models for large scale data mining constitute an exciting development in statistical data analysis which has gained significant momentum in the past decade. Unlike traditional statistical models which often make `i.i.d.' assumptions, graphical models acknowledge dependencies among variables of interest and investigate inference/prediction while taking into account such dependencies. In recent years, latent variable Bayesian networks, such as latent Dirichlet allocation, stochastic block models, Bayesian co-clustering, and probabilistic matrix factorization techniques have achieved unprecedented success in a variety of application domains including... Show More

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