Maximum likelihood estimation of Gaussian mixture models using stochastic search
Pattern Recognition
A hybrid particle swarm optimization approach to bernoulli mixture models
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
A novel clustering algorithm based Gaussian mixture model for image segmentation
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
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We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for arbitrary covariance matrices that allows independent updating of individual parameters while retaining the validity of the matrix. The second solution involves an optimization formulation for finding correspondences between different parameter orderings of candidate solutions. The effectiveness of the proposed solutions are demonstrated on a novel clustering algorithm based on particle swarm optimization for the estimation of Gaussian mixture models.