higrad
Statistical Inference for Online Learning and Stochastic Approximation via HiGrad
Implements the Hierarchical Incremental GRAdient Descent (HiGrad) algorithm, a first-order algorithm for finding the minimizer of a function in online learning just like stochastic gradient descent (SGD). In addition, this method attaches a confidence interval to assess the uncertainty of its predictions. See Su and Zhu (2018) doi:10.48550/arXiv.1802.04876 for details.
- Version0.1.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release03/14/2018
Documentation
Team
Yuancheng Zhu
Weijie Su
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Insights
Last 30 days
This package has been downloaded 134 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,572 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 23 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports1 package