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CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
11 years 3 months ago
Beyond local optimality: An improved approach to hybrid model learning
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Stephanie Gil, Brian Williams
BMCBI
2010
116views more  BMCBI 2010»
11 years 5 months ago
A hybrid approach to protein folding problem integrating constraint programming with local search
Background: The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy func...
Abu Zafer M. Dayem Ullah, Kathleen Steinhöfel
ICML
2005
IEEE
12 years 6 months ago
Robust one-class clustering using hybrid global and local search
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
Gunjan Gupta, Joydeep Ghosh
CVPR
2008
IEEE
12 years 7 months ago
Sparsity, redundancy and optimal image support towards knowledge-based segmentation
In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
Salma Essafi, Georg Langs, Nikos Paragios
ICNC
2005
Springer
11 years 10 months ago
A Game-Theoretic Approach to Competitive Learning in Self-Organizing Maps
Abstract. Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Competitive learning in the SOM training process focusses on ļ¬nding a neu...
Joseph P. Herbert, Jingtao Yao
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