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Friday, June 23 • 3:40pm - 3:52pm
SparseRegression.jl: Statistical Learning in Pure Julia

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SparseRegression implements a variety of offline and online algorithms for statistical models that are linear in the parameters (generalized linear models, quantile regression, SVMs, etc.). This talk will discuss my experience using primitives defined in the JuliaML ecosystem (LossFunctions and PenaltyFunctions) to implement a fast and flexible SparseReg type for fitting a wide variety of models.


Speakers
avatar for Josh Day

Josh Day

NC State University
Josh is a statistics Ph.D. student at NC State University, where he researches on-line optimization algorithms for performing statistical analysis on big and streaming data.


Friday June 23, 2017 3:40pm - 3:52pm
West Pauley Pauley Ballroom, Berkeley, CA