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CORR
2011
Springer
174views Education» more  CORR 2011»
14 years 6 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
POPL
2012
ACM
13 years 9 months ago
A type theory for probability density functions
There has been great interest in creating probabilistic programming languages to simplify the coding of statistical tasks; however, there still does not exist a formal language th...
Sooraj Bhat, Ashish Agarwal, Richard W. Vuduc, Ale...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 2 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
IJCAI
2007
15 years 3 months ago
Inside-Outside Probability Computation for Belief Propagation
In this paper we prove that the well-known correspondence between the forward-backward algorithm for hidden Markov models (HMMs) and belief propagation (BP) applied to HMMs can be...
Taisuke Sato
EUSFLAT
2009
114views Fuzzy Logic» more  EUSFLAT 2009»
15 years 17 hour ago
The Use of Interval-Valued Probability Measures in Fuzzy Linear Programming: a constraint set approach
This paper uses a constraint set approach to linear programming problems with equality constraints whose coefficients and/or right-hand side values could be uncertain. We consider ...
Phantipa Thipwiwatpotjana, Weldon A. Lodwick