Guarantees for Approximate Incremental SVMs
نویسندگان
چکیده
Assume a teacher provides examples one by one. An approximate incremental SVM computes a sequence of classi ers that are close to the true SVM solutions computed on the successive incremental training sets. We show that simple algorithms can satisfy an averaged accuracy criterion with a computational cost that scales as well as the best SVM algorithms with the number of examples. Finally, we exhibit some experiments highlighting the bene ts of joining fast incremental optimization and curriculum and active learning (Schohn & Cohn, 2000; Bordes et al., 2005; Bengio et al., 2009).
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