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Anthony Bourrier

2 accepted papers

2016

Sketching for large-scale learning of mixture models

ICASSP 2016accepted

Learning parameters from voluminous data can be prohibitive in terms of memory and computational requirements. We propose a "compressive learning" framework where we first sketch the data by computing random generalized moments of the underlying probability distribution, then estimate mixture model…

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