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Selective Block Minimization for Faster Convergence of Limited Memory Large-scale Linear Models

Selective Block Minimization for Faster Convergence of Limited Memory Large-scale Linear Models Kai-Wei Chang and Dan Roth. Experiment Settings. Motivation. Linear SVM. The Algorithm. Restrict to use at most 2GB memory. Compared methods: Online methods: VW, Perceptron, MIRA, CW.

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Data block consisting - PowerPoint PPT Presentation

Selective Block Minimization for Faster Convergence of Limited Memory Large-scale Linear Models