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Scalable Training of Mixture Models via Coresets

Scalable Training of Mixture Models via Coresets. Daniel Feldman. Matthew Faulkner. Andreas Krause. MIT. Fitting Mixtures to Massive Data. EM, generally expensive. Weighted EM, fast!. Importance Sample. Coresets for Mixture Models. *. Naïve Uniform Sampling.

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Scalable training of L 1 -regularized log-linear models

Scalable training of L 1 -regularized log-linear models . Galen Andrew (Joint work with Jianfeng Gao) ICML, 2007. Minimizing regularized loss. Many parametric ML models are trained by minimizing a regularized loss of the form: is a loss function quantifying “ fit to the data ”

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527 views • 25 slides

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