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Online Censoring for Large-Scale Regressions with Application to Streaming Big Data
On par with data-intensive applications, the sheer size of modern linear regression problems creates an ever-growing demand for efficient solvers. Fortunately, a significant percentage of the data accrued can be omitted while maintaining a certain quality of statistical inference with an affordable...
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| Publicado no: | IEEE Trans Signal Process |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5198787/ https://ncbi.nlm.nih.gov/pubmed/28042229 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TSP.2016.2546225 |
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