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Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms
Stochastic gradient descent (SGD) is a ubiquitous algorithm for a variety of machine learning problems. Researchers and industry have developed several techniques to optimize SGD’s runtime performance, including asynchronous execution and reduced precision. Our main result is a martingale-based anal...
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| Pubblicato in: | Adv Neural Inf Process Syst |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2015
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4907892/ https://ncbi.nlm.nih.gov/pubmed/27330264 |
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