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Margin-sparsity trade-off for the set covering machine

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2005) 3720 LNAI 206-217
DOI: 10.1007/11564096_23
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Abstract

We propose a new learning algorithm for the set covering machine and a tight data-compression risk bound that the learner can use for choosing the appropriate tradeoff between the sparsity of a classifier and the magnitude of its separating margin. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Laviolette, F., Marchand, M., & Shah, M. (2005). Margin-sparsity trade-off for the set covering machine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3720 LNAI, pp. 206–217). https://doi.org/10.1007/11564096_23

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