@inproceedings{10.1007/978-3-642-04143-3_21,
    abstract = "We propose an algorithm for the problem of training a SVM model when the set of training examples is horizontally distributed across several data sources. The algorithm requires only one pass through each remote source of training examples, and its accuracy and efficiency follow a clear pattern as function of a user-defined parameter. We outline an agent-based implementation of the algorithm. © 2009 Springer Berlin Heidelberg.",
    year = "2009",
    title = "L2-SVM training with distributed data",
    volume = "5774 LNAI",
    pages = "208-213",
    doi = "10.1007/978-3-642-04143-3\_21",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    author = "Lodi, Stefano and Ñanculef, Ricardo and Sartori, Claudio"
}

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