Tempo di lettura: < 1 minuto Taking inspiration from the probabilistic principles underlying the topological regularities observed in random networks, the paper presents a simple and efficient Bayesian framework for the classification

Tempo di lettura: < 1 minuto Supervised models for Word Sense Disambiguation (WSD) currently yield to state-of-the-art results in the most popular benchmarks. Despite the recent introduction of Word

Tempo di lettura: < 1 minuto The paper introduces a dynamic extension of the hybrid random field (HRF), called dynamic HRF (D-HRF). The D-HRF is aimed at the probabilistic

Tempo di lettura: < 1 minuto In this paper we consider several variants of the problem of sorting integer permutations with a minimum number of moves, a task with

Tempo di lettura: < 1 minuto A theory of learning is proposed,which extends naturally the classic regularization framework of kernelmachines to the case in which the agent interacts with

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 form interfaces

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 of First

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, including document

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 Random Fields