During the last years, speed-up techniques for DIJKSTRA’s algorithm have been developed that make the computation of shortest paths a matter of microseconds even on huge road net...
Reinhard Bauer, Gianlorenzo D'Angelo, Daniel Delli...
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
Reliable risk measurement is a key problem for financial institutions and regulatory authorities. The current industry standard Value-at-Risk has several deficiencies. Improved ri...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation be...