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ACIVS
2009
Springer
14 years 5 days ago
A New Feasible Approach to Multi-dimensional Scale Saliency
In this paper, we present a multi-dimensional extension of an image feature extractor, the scale saliency algorithm by Kadir and Brady. In order to avoid the curse of dimensionalit...
Pablo Suau, Francisco Escolano
SAC
2008
ACM
13 years 7 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy
ICASSP
2008
IEEE
14 years 2 months ago
Maximum kernel density estimator for robust fitting
Robust model fitting plays an important role in many computer vision applications. In this paper, we propose a new robust estimator — Maximum Kernel Density Estimator (MKDE) bas...
Hanzi Wang
IDA
2007
Springer
14 years 1 months ago
DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation
The Denclue algorithm employs a cluster model based on kernel density estimation. A cluster is defined by a local maximum of the estimated density function. Data points are assign...
Alexander Hinneburg, Hans-Henning Gabriel
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
13 years 9 months ago
Parsimonious regularization using genetic algorithms applied to the analysis of analytical ultracentrifugation experiments
Frequently in the physical sciences experimental data are analyzed to determine model parameters using techniques known as parameter estimation. Eliminating the effects of noise ...
Emre H. Brookes, Borries Demeler