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Learning rates of gradient descent algorithm for classification

  • Published:2009-02 Issue:1 Volume:224 Page:182-192
  • ISSN:0377-0427
  • Container-title:Journal of Computational and Applied Mathematics
  • language:en
  • Short-container-title:Journal of Computational and Applied Mathematics

Author:

Dong Xue-Mei,Chen Di-Rong

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference22 articles.

1. Theory of reproducing kernels;Aronszajn;Trans. Amer. Math. Soc.,1950

2. Relative loss bounds for on-line density estimation with exponential family of distributions;Azoury;Mach. Learn.,2001

3. Convexity, classification and risk bounds;Bartlett;J. Amer. Statist. Assoc.,2006

4. Rademacher and Gaussian complexities: Risk bounds and structural results;Bartlett;J. Mach. Learn. Res.,2002

5. Stability and generalization;Bousquet;J. Mach. Learn. Res.,2002

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2. Strong Convex Loss Can Increase the Learning Rates of Online Learning;Journal of Computers;2014-07-01

3. Error Analysis of Stochastic Gradient Descent Ranking;IEEE Transactions on Cybernetics;2013-06

4. LEAST SQUARE REGRESSION WITH COEFFICIENT REGULARIZATION BY GRADIENT DESCENT;International Journal of Wavelets, Multiresolution and Information Processing;2012-01

5. Approximation Analysis of Gradient Descent Algorithm for Bipartite Ranking;Journal of Applied Mathematics;2012
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