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ICASSP
2011
IEEE
14 years 4 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
109
Voted
CVPR
2010
IEEE
15 years 9 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
102
Voted
CCGRID
2008
IEEE
15 years 7 months ago
Grid Differentiated Services: A Reinforcement Learning Approach
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
112
Voted
GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
15 years 4 months ago
Linguistic Rule Extraction by Genetics-Based Machine Learning
This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algori...
Hisao Ishibuchi, Tomoharu Nakashima
FECS
2007
184views Education» more  FECS 2007»
15 years 2 months ago
Collaboratory: An Open Source Teaching and Learning Facility for Computer Science and Engineering Education
In this paper we present an innovative prototype Open Source Teaching/Learning Collaboratory created at UC Merced that will provide the foundation for offering the vast majority of...
Jeff Wright, Stefano Carpin, Alberto Cerpa, German...