The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Pairwise data clustering by deterministic annealing
Abstract
Partitioning a data set and extracting hidden structure from the data arises in different application areas of pattern recognition, speech and image processing. Pairwise data clustering is a combinatorial optimization method for data grouping which extracts hidden structure from proximity data. We describe a deterministic annealing approach to pairwise clustering which shares the robustness properties of maximum entropy inference. The resulting Gibbs probability distributions are estimated by mean-field approximation. A new structure-preserving algorithm to cluster dissimilarity data and to simultaneously embed these data in a Euclidian vector space is discussed which can be used for dimensionality reduction and data visualization. The suggested embedding algorithm which outperforms conventional approaches has been implemented to analyze dissimilarity data from protein analysis and from linguistics. The algorithm for pairwise data clustering is used to segment textured images.
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Citations
Cites
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A graduated assignment algorithm for graph matching
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Cited by
Maximum entropy modeling of species geographic distributions
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2005.03.026 · Cited by 15,396
A statistical explanation of MaxEnt for ecologists
Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., & Yates, C. J. (2011) · Diversity and Distributions · doi:10.1111/j.1472-4642.2010.00725.x · Cited by 6,699
A new point matching algorithm for non-rigid registration
Chui, H., & Rangarajan, A. (2003) · Computer Vision and Image Understanding · doi:10.1016/s1077-3142(03)00009-2 · Cited by 1,560
Yuille, A. L., & Rangarajan, A. (2003) · Neural Computation · doi:10.1162/08997660360581958 · Cited by 1,151
(1999) · Cited by 397
Data Mined Ionic Substitutions for the Discovery of New Compounds
Hautier, G., Fischer, C., Ehrlacher, V., Jain, A., & Ceder, G. (2011) · Inorganic Chemistry · doi:10.1021/ic102031h · Cited by 394
Grouping with Asymmetric Affinities: A Game-Theoretic Perspective
Torsello, A., Bulo, S. R., & Pelillo, M. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.130 · Cited by 71
Revealing Free Energy Landscape From MD Data via Conditional Angle Partition Tree
Jiang, H., Li, H., Wong, W. H., & Fan, X. (2023) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3172352 · Cited by 4
Metadata
- Authors
- Hofmann, T., & Buhmann, J. M.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1997
- Volume
- 19
- Issue
- 1
- Pages
- 1-14
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2077990749
- Cited by
- 451
- References
- 8
- FWCI
- 20.92
- Type
- journal article
- Language
- en
- Open access
- closed
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