Abstract: We present closed-form expressions for marginalizing and conditioning Gaussians onto linear manifolds, and demonstrate how to apply these expressions to smooth non-linear manifolds through ...

Abstract: We consider the problem of online sparse linear approximation, where a learner sequentially predicts the best sparse linear approximations of an as yet unobserved sequence of measurements in ...