Search results for "working sets"

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Dual Extrapolation for Sparse Generalized Linear Models

2020

International audience; Generalized Linear Models (GLM) form a wide class of regression and classification models, where prediction is a function of a linear combination of the input variables. For statistical inference in high dimension, sparsity inducing regularizations have proven to be useful while offering statistical guarantees. However, solving the resulting optimization problems can be challenging: even for popular iterative algorithms such as coordinate descent, one needs to loop over a large number of variables. To mitigate this, techniques known as screening rules and working sets diminish the size of the optimization problem at hand, either by progressively removing variables, o…

FOS: Computer and information sciencesComputer Science - Machine Learningextrapolation[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Machine Learning (stat.ML)working setsgeneralized linear models[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]Convex optimizationscreening rulesMachine Learning (cs.LG)[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Statistics - Machine Learning[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Lassosparse logistic regression
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