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NIPS
1994
15 years 7 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
Mario Marchand, Saeed Hadjifaradji
BMCBI
2010
150views more  BMCBI 2010»
15 years 6 months ago
Systematic calibration of a cell signaling network model
Background: Mathematical modeling is being applied to increasingly complex biological systems and datasets; however, the process of analyzing and calibrating against experimental ...
Kyoung Ae Kim, Sabrina L. Spencer, John G. Albeck,...
LATA
2010
Springer
16 years 1 months ago
Extending Stochastic Context-Free Grammars for an Application in Bioinformatics
We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the subword that is generated from the application and sho...
Frank Weinberg, Markus E. Nebel
ECML
2003
Springer
15 years 11 months ago
A Hybrid Language Model based on Stochastic Context-free Grammars
Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
Diego Linares, José-Miguel Benedí, J...
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 5 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...