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...
Belief propagation (BP) is an effective algorithm for solving energy minimization problems in computer vision. However, it requires enormous memory, bandwidth, and computation beca...
Chao-Chung Cheng, Chia-Kai Liang, Homer H. Chen, L...
This paper addresses the “boundary ownership” problem,
also known as the figure/ground assignment problem.
Estimating boundary ownerships is a key step in perceptual
organiz...
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...