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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
BMCBI
2010
229views more  BMCBI 2010»
13 years 7 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
ISPASS
2009
IEEE
14 years 2 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
ECCV
2006
Springer
14 years 9 months ago
A Tuned Eigenspace Technique for Articulated Motion Recognition
In this paper, we introduce a tuned eigenspace technique so as to classify human motion. The method presented here overcomes those problems related to articulated motion and dress...
M. Masudur Rahman, Antonio Robles-Kelly
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolutionary change in developmental timing
This paper presents a mutation-based evolutionary algorithm that evolves genotypic genes for regulating developmental timing of phenotypic values. The genotype sequentially genera...
Kei Ohnishi, Kaori Yoshida