Abstract. We adopt Benders’ decomposition algorithm to solve scenariobased Stochastic Constraint Programs (SCPs) with linear recourse. Rather than attempting to solve SCPs via a ...
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learnin...
Abstract. We study three comparison-based problems related to multisets in the cache-oblivious model: Duplicate elimination, multisorting and finding the most frequent element (th...
Arash Farzan, Paolo Ferragina, Gianni Franceschini...
We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), which are classes of (finitely presented) countable-state MDPs and zero-su...
In this paper we address two optimization problems arising in the design of genomic assays based on universal tag arrays. First, we address the universal array tag set design probl...