We present a system-level approach for power optimization under a set of user specified costs and timing constraints of hard real-time designs. The approach optimizes all three d...
We present a new approach to pricing American-style derivatives that is applicable to any Markovian setting (i.e., not limited to geometric Brownian motion) for which European cal...
Scott B. Laprise, Michael C. Fu, Steven I. Marcus,...
Workflow mining is the task of automatically producing a workflow model from a set of event logs recording sequences of workflow events; each sequence corresponds to a use case or ...
Javier Esparza, Martin Leucker, Maximilian Schlund
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
We introduce the classified stable matching problem, a problem motivated by academic hiring. Suppose that a number of institutes are hiring faculty members from a pool of applican...