Local convergence analysis of a grouped variable version of coordinate descent
Journal of Optimization Theory and Applications
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Local convergence of tri-level alternating optimization
Neural, Parallel & Scientific Computations
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Will the real iris data please stand up?
IEEE Transactions on Fuzzy Systems
Optimization of clustering criteria by reformulation
IEEE Transactions on Fuzzy Systems
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
Global optimization in clustering using hyperbolic cross points
Pattern Recognition
Anisotropic mean shift based fuzzy c-means segmentation of skin lesions
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
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The efficiency of optimization in fuzzy c-means clustering is investigated. Numerous, powerful, general-purpose simultaneous optimization (SO) methods, and hybrid methods combining these and the most widely used alternating optimization (AO) method, are extensively tested for speed comparison. AO is clearly the best and simplest of the methods we tested when used on data sets of small or moderate sizes, especially those containing well-separated clusters. This justifies the extremely wide use of AO. On large-scale problems, some methods we tested are significantly faster than AO.