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» A New Discriminative Kernel From Probabilistic Models
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PE
2000
Springer
118views Optimization» more  PE 2000»
14 years 11 months ago
A probabilistic dynamic technique for the distributed generation of very large state spaces
Conventional methods for state space exploration are limited to the analysis of small systems because they suffer from excessive memory and computational requirements. We have dev...
William J. Knottenbelt, Peter G. Harrison, Mark Me...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
15 years 5 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
IJCAI
2007
15 years 1 months ago
Graph-Based Semi-Supervised Learning as a Generative Model
This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
Jingrui He, Jaime G. Carbonell, Yan Liu 0002
IBPRIA
2003
Springer
15 years 5 months ago
Smoothing Techniques for Tree-k-Grammar-Based Natural Language Modeling
Abstract. In a previous work, a new probabilistic context-free grammar (PCFG) model for natural language parsing derived from a tree bank corpus has been introduced. The model esti...
Jose L. Verdú-Mas, Jorge Calera-Rubio, Rafa...
BMCBI
2007
135views more  BMCBI 2007»
14 years 12 months ago
Sequence similarity is more relevant than species specificity in probabilistic backtranslation
Background: Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module....
Alfredo Ferro, Rosalba Giugno, Giuseppe Pigola, Al...