Speaker: Addison Hu

Abstract: Functions of bounded variation (BV) arise in diverse settings such as image recovery (where the 2D function to be modeled is BV) and locally adaptive regression splines/trend filtering (where the kth weak derivative of the estimator is BV). In this talk I will discuss the problem of estimating a BV function in R^d using scattered data, and along the way discuss various continuous & discrete notions of total variation and how they relate to each other. Based on work in-progress with Alden Green and Ryan Tibshirani.