Titlebook: Artificial Intelligence Applications in Information and Communication Technologies; Yacine Laalaoui,Nizar Bouguila Book 2015 Springer Inte

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1860-949X ok is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems. . .978-3-319-36526-8978-3-319-19833-0Series ISSN 1860-949X Series E-ISSN 1860-9503

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Prologue: The Correspondence PrincipleDirichlet mixture which provides a natural way of clustering positive data. An EM-style algorithm is developed based upen variational inference for learning the parameters of the mixture model. The proposed statistical framework is applied to the challenging tasks of natural scene categorization and human activity classification.

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A Formal Treatment of Case Studiesmany cases, a given user does not possess the adequate tools and semantics to express what he/she is looking for, thus, his/her target image resides in his/her mind while he/she can visually identify it. We propose in this work, a statistical framework that enables users to start a search process an

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Prologue: The Correspondence Principlech suite of models and techniques. In particular, finite mixture models have received a lot of attention by offering a formal approach to unsupervised learning which allows to discover the latent structure expressed in observed data. In this chapter, we propose a mixture model based on the inverted

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Agustín Vicente,Fernando Martínez-Manriquestributions provide a flexible and convenient class of models for density estimation and their statistical learning has been studied extensively. In this context, fully Bayesian approaches have been widely adopted for mixture estimation and model selection problems and have shown some effectiveness