We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
We propose a novel consistent max-covering scheme for
human pose estimation. Consistent max-covering formulates
pose estimation as the covering of body part polygons
on an objec...
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...