In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
A post-processor is an integral part of any OCR system. This paper proposes a method for detection and correction of errors in recognition results of handwritten and machine print...
Resource virtualization is currently being employed at all levels of the IT infrastructure to improve provisioning and manageability, with the goal of reducing total cost of owner...
We consider scheduling problems in which a job consists of components of different types to be processed on m machines. Each machine is capable of processing components of a singl...