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GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
13 years 12 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
ISMIR
2005
Springer
164views Music» more  ISMIR 2005»
14 years 25 days ago
Theory and Evaluation of a Bayesian Music Structure Extractor
We introduce a new model for extracting classified structural segments, such as intro, verse, chorus, break and so forth, from recorded music. Our approach is to classify signal ...
Samer A. Abdallah, Katy Noland, Mark B. Sandler, M...
ALIFE
1999
13 years 7 months ago
A New Structurally Dissolvable Self-Reproducing Loop Evolving in a Simple Cellular Automata Space
tion, structural dissolutionAbstract We constructed a simple evolutionary system, "evoloop," on a deterministic nine-state five-neighbor cellular automata (CA) space by i...
Hiroki Sayama
INFSOF
2007
74views more  INFSOF 2007»
13 years 7 months ago
Software process improvement as emergent change: A structurational analysis
This paper presents a framework that draws on Structuration theory and dialectical hermeneutics to explicate the dynamics of software process improvement (SPI) in a packaged softw...
I. Allison, Yasmin Merali
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
13 years 5 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi