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sgd: Stochastic Gradient Descent for Scalable Estimation
A fast and flexible set of tools for large scale estimation. It features many stochastic gradient methods, built-in models, visualization tools, automated hyperparameter tuning, model checking, interval estimation, and convergence diagnostics.
Getting started
Browse package contents
Package details |
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| Author | Junhyung Lyle Kim [cre, aut], Dustin Tran [aut], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb] |
| Maintainer | Junhyung Lyle Kim <jlylekim@gmail.com> |
| License | GPL-2 |
| Version | 1.1.2 |
| URL | https://github.com/airoldilab/sgd |
| Package repository | View on CRAN |
| Installation |
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