iCotoba

**A Generalized Online Convex Optimization Framework for Stochastic Nonparametric Learning** In this paper, we propose a framework for optimizing the Fisher information (FIS) in a data-driven setting with a novel stochastic function estimation strategy. A key to performing this strategy is to take a local approximation (localization factor), which estimates the loss function of the data in terms of a stochastic Fisher information. We show the effectiveness of our framework using two simulated instances where the Fisher information is not …