In this paper we consider a class of regularized Gauss-Newton methods for solving nonlinear inverse problems for which an a posteriori stopping rule is proposed to terminate the it...
We consider the methods xδ n+1 = xδ n − gαn (F (xδ n)∗F (xδ n))F (xδ n)∗(F (xδ n)− yδ) for solving nonlinear ill-posed inverse problems F (x) = y using the only ava...
We propose an efficient solution to the general M-view projective reconstruction problem, using matrix factorization and iterative least squares. The method can accept input with ...
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...