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Discriminative k-metrics

Publication ,  Journal Article
Szlam, A; Sapiro, G
Published in: ACM International Conference Proceeding Series
September 15, 2009

The k q-flats algorithm is a generalization of the popular k-means algorithm where q dimensional best fit affine sets replace centroids as the cluster prototypes. In this work, a modification of the k q-flats framework for pattern classification is introduced. The basic idea is to replace the original reconstruction only energy, which is optimized to obtain the k affine spaces, by a new energy that incorporates discriminative terms. This way, the actual classification task is introduced as part of the design and optimization. The presentation of the proposed framework is complemented with experimental results, showing that the method is computationally very efficient and gives excellent results on standard supervised learning benchmarks. Copyright 2009.

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Published In

ACM International Conference Proceeding Series

DOI

Publication Date

September 15, 2009

Volume

382
 

Citation

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Szlam, A., & Sapiro, G. (2009). Discriminative k-metrics. ACM International Conference Proceeding Series, 382. https://doi.org/10.1145/1553374.1553503
Szlam, A., and G. Sapiro. “Discriminative k-metrics.” ACM International Conference Proceeding Series 382 (September 15, 2009). https://doi.org/10.1145/1553374.1553503.
Szlam A, Sapiro G. Discriminative k-metrics. ACM International Conference Proceeding Series. 2009 Sep 15;382.
Szlam, A., and G. Sapiro. “Discriminative k-metrics.” ACM International Conference Proceeding Series, vol. 382, Sept. 2009. Scopus, doi:10.1145/1553374.1553503.
Szlam A, Sapiro G. Discriminative k-metrics. ACM International Conference Proceeding Series. 2009 Sep 15;382.

Published In

ACM International Conference Proceeding Series

DOI

Publication Date

September 15, 2009

Volume

382