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Stochastic Gradient Descent and the Prediction of MeSH for PubMed Records
Stochastic Gradient Descent (SGD) has gained popularity for solving large scale supervised machine learning problems. It provides a rapid method for minimizing a number of loss functions and is applicable to Support Vector Machine (SVM) and Logistic optimizations. However SGD does not provide a conv...
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| Pubblicato in: | AMIA Annu Symp Proc |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
American Medical Informatics Association
2014
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4419959/ https://ncbi.nlm.nih.gov/pubmed/25954431 |
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