Classification with partially labeled data requires using a large number of unlabeled examples (or an estimated marginal P (x)), to further constrain the conditional P (y|x) beyond a few available labeled examples. We formulate a regularization approach to linking the marginal and the conditional in a general way. The regularization penalty measures the information that is implied about the lab...

0167-8655/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.patrec.2010.09.004 ⇑ Corresponding author. Address: National Centre f okritos”, Athens, Greece. Tel.: +302106503204; fax: + E-mail address: [email protected] (A. Kri In this paper, we address the problem of learning aspect models with partially labeled data for the task of document categorization. The motivation of this w...

The importance of Markov blanket discovery algorithms is twofold: as the main building block in constraint-based structure learning of Bayesian network algorithms and as a technique to derive the optimal set of features in filter feature selection approaches. Equally, learning from partially labelled data is a crucial and demanding area of machine learning, and extending techniques from fully t...

Deterministic compartmental models are predominantly used in the modeling of infectious diseases, though stochastic considered more realistic, yet complicated to estimate due missing data. In this paper we present a novel algorithm for estimating Susceptible-Infected-Recovered and Susceptible-Exposed-Infected-Recovered (SIR/SEIR) epidemic model within Bayesian framework, which can be readily ex...

background: chronic idiopathic urticaria is defined as urticaria, which lasts for more than 8 weeks and has no apparent etiology. the aim of this study was to examine the causal role of helicobacter pylori infection in chronic idiopathic urticaria.   methods: fifty-six patients with chronic idiopathic urticaria and a negative response to skin prick test for common aeroallergens were selected. t...