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) <arXiv:1802.04876> for details.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling source/ R- | higrad_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
rolling linux/jammy R-4.5 | higrad_0.1.0.tar.gz |
29.4 KiB |
0.1.0 |
rolling linux/noble R-4.5 | higrad_0.1.0.tar.gz |
29.3 KiB |
0.1.0 |
latest source/ R- | higrad_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
latest linux/jammy R-4.5 | higrad_0.1.0.tar.gz |
29.4 KiB |
0.1.0 |
latest linux/noble R-4.5 | higrad_0.1.0.tar.gz |
29.3 KiB |
0.1.0 |
2026-04-23 source/ R- | higrad_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | higrad_0.1.0.zip |
32.2 KiB |
0.1.0 |
2025-04-20 source/ R- | higrad_0.1.0.tar.gz |
6.3 KiB |