Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
We consider models for bargaining in social networks, in which players are represented by vertices and edges represent bilateral opportunities for deals between pairs of players. ...
Tanmoy Chakraborty, Michael Kearns, Sanjeev Khanna
We address visual correspondence problems without assuming that scene points have similar intensities in different views.This situation is common, usually due to non-lambertian sc...
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Many embedded systems use a simple pipelined RISC processor for computation and an on-chip SRAM for data storage. We present an enhancement called Intelligent SRAM (ISRAM) that co...