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arXiv · 1602.01124

Non accelerated efficient numerical methods for sparse quadratic optimization problems and its generalizations

Anton Anikin·Alexander Gasnikov·Alexander Gornov
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Abstract

We investigate primal gradient method with l1-norm and conditional gradient method (both methods are non accelerated). We show that these methods can outperform well known accelerated approaches for some classes of sparse quadratic problems. Moreover we discuss some generalizations.

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Anton Anikin, Alexander Gasnikov, Alexander Gornov. 2016-02-02. Non accelerated efficient numerical methods for sparse quadratic optimization problems and its generalizations. https://arxiv.org/abs/1602.01124

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