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CORR
2011
Springer
174views Education» more  CORR 2011»
12 years 11 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
12 years 3 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»
13 years 7 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
13 years 9 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»
13 years 5 months 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