In this paper we tackle the problem of providing a mobile robot with the ability to build a map of its environment using data gathered during navigation. The data correspond to the...
We present new explicit constructions of deterministic randomness extractors, dispersers and related objects. We say that a distribution X on binary strings of length n is a -sour...
Boaz Barak, Guy Kindler, Ronen Shaltiel, Benny Sud...
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Abstract. We present a probabilistic model for robust principal component analysis (PCA) in which the observation noise is modelled by Student-t distributions that are independent ...
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...