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.