LEARNING RATES FOR DENSITY LEVEL DETECTION
Clint Scovel, Don R. Hush, Ingo Steinwart · Analysis and Applications · 2005
In this paper, we address learning rates for the density level detection (DLD) problem. We begin by proving a "No Free Lunch Theorem" showing that rates cannot be obtained in general. Then, we apply a recently established classification framework to obtain rates for DLD support vector machines under mild assumptions on the density.