In this paper, we consider the problem of estimating an unknown deterministic parameter vector in a linear regression model with random Gaussian uncertainty in the mixing matrix. W...
Statistical data frequently includes outliers; these can distort the results of estimation procedures and optimization problems. For this reason, loss functions which deemphasize ...
Unbiased and consistent estimates of structure and motion can be obtained by least squares minimization of the differential epipolar constraint. Previous work on this subject does...
Abstract— In this paper, we address the problem of determining the relative position and orientation (pose) of two robots navigating in 2D, based on known egomotion and noisy rob...
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...