Mathematics of Operations Research, Vol. 18, No. 1 (Feb., 1993), pp. 71-97 (27 pages) This paper is concerned with the design and probabilistic analysis of algorithms for the maximum-flow problem and ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

In the Vehicle Routing Problem with Time Windows, a set of customers are served by a fleet of vehicles of limited capacity, initially located at a central depot. Each customer provides a period of ...