Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
A robust and effective feature map integration method is presented for infrared (IR) target recognition. Noise in an IR image makes a target recognition system unstable in pose es...
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...