Variable Metric Stochastic Approximation Theory
We provide a variable metric stochastic approximation theory. In doing so, we provide a convergence theory for a large class of online variable metric methods including the recently introduced online versions of the BFGS algorithm and its limited-memory LBFGS variant. We also discuss the implications of our results for learning from expert advice.
|Collections||ANU Research Publications|
|Source:||Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS 2009)|