Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources
15 Maggio 2018Tempo 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…
Leggi tuttoDynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics
1 Ottobre 2017Tempo 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…
Leggi tuttoOptimally solving permutation sorting problems with efficient partial expansion bidirectional heuristic search
30 Maggio 2016Tempo 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…
Leggi tuttoLearning as Constraint Reactions
15 Settembre 2015Tempo 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…
Leggi tuttoExperimental Guidelines for Semantic-Based Regularization
15 Aprile 2014Tempo 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…
Leggi tuttoImproved multi-level protein–protein interaction prediction with semantic-based regularization
15 Aprile 2014Tempo 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…
Leggi tuttoSemi-supervised clustering methods
1 Luglio 2013Tempo 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,…
Leggi tuttoTowards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning
23 Dicembre 2012Tempo 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…
Leggi tuttoTowards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation
23 Novembre 2012Tempo 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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