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» Shapes as empirical distributions
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AAAI
2012
13 years 4 days ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
IJCNN
2006
IEEE
15 years 3 months ago
Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method
— Neuronal morphology plays a crucial role in the information processing capabilities of neurons. Despite the importance of morphology for neural functionality, biological data i...
Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma
GI
2001
Springer
15 years 2 months ago
Designing QoS and Charging Mechanisms: He who pays the service shapes the design
To accommodate applications with highly variable degrees and categories of Quality of Service (QoS) requirements, a major effort has been invested to overcome the traditional best-...
Anna Bouch, Martina Angela Sasse
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
14 years 10 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
BMCBI
2010
151views more  BMCBI 2010»
14 years 10 months ago
Using diffusion distances for flexible molecular shape comparison
Background: Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat t...
Yu-Shen Liu, Qi Li, Guo-Qin Zheng, Karthik Ramani,...