A variable metric proximal stochastic gradient method: An application to classification problems
Due to the continued success of machine learning and deep learning in particular, supervised classification problems are ubiquitous in numerous scientific fields. Training these models typically involves the minimization of the empirical risk over large data sets along with a possibly non-differenti...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-01-01
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| Series: | EURO Journal on Computational Optimization |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2192440624000054 |
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