Linear Programming (LP) relaxations have become powerful tools for finding the most probable (MAP) configuration in graphical models. These relaxations can be solved efficiently u...
David Sontag, Talya Meltzer, Amir Globerson, Tommi...
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...
—The multiple-access framework of ZigZag decoding [1] is a useful technique for combating interference via multiple repeated transmissions, and is known to be compatible with dis...
Arash Saber Tehrani, Alexandros G. Dimakis, Michae...
In this paper, we propose a series of techniques to enhance the computational performance of existing Belief Propagation (BP) based stereo matching that relies on automatic estima...
Shafik Huq, Andreas Koschan, Besma R. Abidi, Mongi...