Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good per...
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the...
We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the `best' one? and the second one:...
We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values i...
The memory dumping problem arises in the context of planning and scheduling activities of the Mars Express mission of the European Space Agency. The problem consists of scheduling...