<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Statistical Inference for Online Learning and Stochastic
Approximation via HiGrad</dc:title>
  <dc:title>R package higrad version 0.1.0</dc:title>
  <dc:description>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) &lt;arXiv:1802.04876&gt; for details. </dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: Matrix</dc:relation>
  <dc:creator>Yuancheng Zhu &lt;yuancheng.zhu@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Weijie Su [aut],
  Yuancheng Zhu [aut, cre]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2018-03-14</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=higrad</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.higrad</dc:identifier>
</oai_dc:dc>
