Robust Computation of Linear Models, or How to Find a Needle in a Haystack
Robust Computation of Linear Models, or How to Find a Needle in a Haystack
Consider a dataset of vector-valued observations that consists of noisy inliers, which are explained well by a low-dimensional subspace, along with some number of outliers.This work describes a convex optimization problem, called REAPER, that can reliably fit a low-dimensional model to this type of data.This approach parameterizes linear subspaces using …