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Convergence results for the EM approach to mixtures of experts architectures
Open accessAbstract
The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts architecture of Jacobs, Jordan, Nowlan and Hinton (1991) and the hierarchical mixture of experts architecture of Jordan and Jacobs (1992). They showed empirically that the EM algorithm for these architectures yields significantly faster convergence than gradient ascent. In the current paper we provide a theoretical analysis of this algorithm. We show that the algorithm can be regarded as a variable metric algorithm with its searching direction having a positive projection on the gradient of the log likelihood. We also analyze the convergence of the algorithm and provide an explicit expression for the convergence rate. In addition, we describe an acceleration technique that yields a significant speedup in simulation experiments.
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Cited by
EEG signal classification using wavelet feature extraction and a mixture of expert model.
SUBASI, A. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.02.005 · Cited by 1,182
Twenty Years of Mixture of Experts
Yuksel, S. E., Wilson, J. N., & Gader, P. D. (2012) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2012.2200299 · Cited by 606
Huo, Z., PakBin, A., Chen, X., Hurley, N., Yuan, Y., Qian, X., Wang, Z., Huang, S., & Mortazavi, B. (2020) · arXiv · doi:10.48550/arxiv.2003.01753 · Cited by 10
Metadata
- Authors
- Jordan, M. I., & Xu, L.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 1995-01
- Volume
- 8
- Issue
- 9
- Pages
- 1409-1431
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2011277999
- Cited by
- 305
- References
- 0
- FWCI
- 15.32
- Type
- journal article
- Language
- en
- Open access
- green
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- Jordan, M. I., & Xu, L. (1995). Convergence results for the EM approach to mixtures of experts architectures. Neural Networks. https://doi.org/10.1016/0893-6080(95)00014-3
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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