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Online Learning Algorithms

Abstract

In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHSs) and general Hilbert spaces. We present a general form of the stochastic gradient method to minimize a quadratic potential function by an independent identically distributed (i.i.d.) sample sequence, and show a probabilistic upper bound for its convergence.

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Correspondence to Steve Smale or Yuan Yao.

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Smale, S., Yao, Y. Online Learning Algorithms. Found Comput Math 6, 145–170 (2006). https://doi.org/10.1007/s10208-004-0160-z

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  • DOI: https://doi.org/10.1007/s10208-004-0160-z

  • Online learning
  • Stochastic approximation
  • Regularization
  • Reproducing Kernel Hilbert Spaces