NEWS

Experimental Guidelines for Semantic-Based Regularization
15 Aprile 2014

Tempo di lettura: < 1 minuto This paper presents a novel approach for learning with constraints called Semantic-Based Regularization. This paper shows how prior knowledge in form…

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Improved multi-level protein–protein interaction prediction with semantic-based regularization
15 Aprile 2014

Tempo di lettura: < 1 minuto Protein–protein interactions can be seen as a hierarchical process occurring at three related levels: proteins bind by means of specific domains, which in turn…

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Semi-supervised clustering methods
1 Luglio 2013

Tempo di lettura: < 1 minuto Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications,…

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Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning
23 Dicembre 2012

Tempo di lettura: < 1 minuto Probabilistic graphical modeling via Hybrid Random Fields (HRFs) was introduced recently, and shown to improve over Bayesian Networks (BNs) and Markov…

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Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation
23 Novembre 2012

Tempo di lettura: < 1 minuto This paper develops a maximum pseudo-likelihood algorithm for learning the structure of the dynamic extension of Hybrid Random Field introduced in…

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