—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
We consider multi-class blocking systems in which jobs require a single processing step. There are groups of servers that can each serve a different subset of all job classes. The...
Large-scale military deployments require transporting equipment and personnel over long distances in a short time. Planning an efficient airlift system is complicated and several ...
Julien Granger, Ananth Krishnamurthy, Stephen M. R...
We consider a traffic-groomed optical network consisting of N nodes arranged in tandem. This optical network is modeled by a tandem queueing network of multi-rate loss queues with...
Alicia Nicki Washington, Chih-Chieh Hsu, Harry G. ...