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<item>
  <id>05384217</id>
  <dt>j</dt>
  <an>05384217</an>
  <augroup>
    <au>Taniguchi, Michiaki</au>
    <au>Tresp, Volker</au>
  </augroup>
  <ti>Averaging regularized estimators.</ti>
  <so>Neural Comput. 9, No. 5, 1163-1178 (1997).</so>
  <py>1997</py>
  <pu>MIT Press, Cambridge, MA</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
    <cc>I.2.6</cc>
    <cc>G.1</cc>
  </ccgroup>
  <utgroup>
    <ut>neural network</ut>
    <ut>training</ut>
    <ut>estimator performance</ut>
    <ut>regularization</ut>
    <ut>averaging</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1162/neco.1997.9.5.1163</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We compare the performance of averaged regularized estimators. We show that the improvement in performance can be achieved by averaging depends critically on the degree of regularization which is used in training the individual estimators. (Provider: Leibiger)</ab>
    <rv></rv>
  </abgroup>
</item>