Generalized Belief Propagation (gbp) has proven to be a promising technique for performing inference on Markov random fields (mrfs). However, its heavy computational cost and large...
A fundamental problem in signal processing is to estimate signal from noisy observations. When some prior information about the statistical models of the signal and noise is avail...
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f : N0 → Z. This is an optimization problem, where both wron...
Model-based interface development systems have not been able to progress beyond producing narrowly focused interface designs of restricted applicability. We identify a -abstractio...