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» Bottom-up learning of Markov logic network structure
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ICANN
2009
Springer
15 years 2 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
JMLR
2010
140views more  JMLR 2010»
14 years 4 months ago
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
ICASSP
2008
IEEE
15 years 3 months ago
Bayesian update of dialogue state for robust dialogue systems
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
Blaise Thomson, Jost Schatzmann, Steve Young
RECOMB
2007
Springer
15 years 9 months ago
A Feature-Based Approach to Modeling Protein-DNA Interactions
Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position spe...
Eilon Sharon, Eran Segal
WWW
2008
ACM
15 years 10 months ago
Automatically refining the wikipedia infobox ontology
The combined efforts of human volunteers have recently extracted numerous facts from Wikipedia, storing them as machine-harvestable object-attribute-value triples in Wikipedia inf...
Fei Wu, Daniel S. Weld