Efficient Splitting and Merging Algorithms for Order Decomposable Problems
β Scribed by Roberto Grossi; Giuseppe F. Italiano
- Book ID
- 112252446
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 503 KB
- Volume
- 154
- Category
- Article
- ISSN
- 0890-5401
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π SIMILAR VOLUMES
In order to alleviate the problem of local convergence of the usual EM algorithm, a split-and-merge operation is introduced into the EM algorithm for Gaussian mixtures. The split-and-merge equations are ΓΏrst presented theoretically. These equations show that the merge operation is a well-posed probl
The maximum-likelihood estimate of a mixture model is usually found by using the EM algorithm. However, the EM algorithm suffers from the local-optimum problem and therefore we cannot obtain the potential performance of mixture models in practice. In the case of mixture models, local maxima often in