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» Solution Methods for a New Class of Simple Model Neurons
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117
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CEC
2007
IEEE
15 years 9 months ago
Bayesian inference in estimation of distribution algorithms
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
105
Voted
SIGGRAPH
1995
ACM
15 years 7 months ago
Depicting fire and other gaseous phenomena using diffusion processes
Developing a visually convincing model of fire, smoke, and other gaseousphenomenais among the most difficult and attractive problems in computer graphics. We have created new me...
Jos Stam, Eugene Fiume
126
Voted
CVPR
2008
IEEE
16 years 5 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
130
Voted
GLOBECOM
2006
IEEE
15 years 9 months ago
A Coverage-Preserving and Hole Tolerant Based Scheme for the Irregular Sensing Range in Wireless Sensor Networks
— Coverage is an important issue related to WSN quality of service. Several centralized/decentralized solutions based on the geometry information of sensors and under the assumpt...
Azzedine Boukerche, Xin Fei, Regina Borges de Arau...
137
Voted
DAGM
2010
Springer
15 years 4 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen