A0962
Title: Cross-validation for signal denoising
Authors: Sabyasachi Chatterjee - University of Illinois at Urbana Champaign (United States) [presenting]
Abstract: A general cross-validation framework for signal denoising is discussed. We will then discuss how to apply this framework to two non parametric regression methods Trend Filtering and Dyadic CART. The resulting cross-validated versions would attain nearly the same rates of convergence as are known for the optimally tuned analogues. There did not exist any previous theoretical analyses of cross validated versions of Trend Filtering or Dyadic CART before this work. This framework is very general and potentially applicable to a wide range of estimation methods which use tuning parameters.
