This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking pr...
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Abstract--To achieve a high product quality for nano-scale systems both realistic defect mechanisms and process variations must be taken into account. While existing approaches for...
With the advent of high-performance COTS clusters, there is a need for a simple, scalable and faulttolerant parallel programming and execution paradigm. In this paper, we show that...
Reza Farivar, Abhishek Verma, Ellick Chan, Roy H. ...
We propose a gossip-based distributed algorithm for Gaussian mixture learning, Newscast EM. The algorithm operates on network topologies where each node observes a local quantity ...