Online Learning Algorithms

In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHS) 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.

• Type: Journal
• Year: 2006
• Where: FOCM
• Authors: Steve Smale, Yuan Yao
• Keywords: FOCM 2006, Probabilistic Upper Bound, Quadratic Potential Function, Stochastic Gradient Method