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Documents Associated With Scientific Events Year : 2017

Random Moments for Sketched Mixture Learning

Abstract

We present a method to solve large-scale mixture learning tasks from a sketch of the data, formed by random generalized empirical moments. We give empirical and theoretical results on k-means and Gaussian Mixture Model estimation problems.
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Dates and versions

hal-01494045 , version 1 (22-03-2017)

Identifiers

  • HAL Id : hal-01494045 , version 1

Cite

Nicolas Keriven, Rémi Gribonval, Gilles Blanchard, Yann Traonmilin. Random Moments for Sketched Mixture Learning. SPARS2017 - Signal Processing with Adaptive Sparse Structured Representations workshop, Jun 2017, Lisbon, Portugal. ⟨hal-01494045⟩
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