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We analyze a short-term revenue optimization problem that involves the optimal targeting of customers for a promotion in which a finite number of perishable items are sold on a last-minute offer. The goal is to select the subset of customers to whom the of ...
A discretization scheme for a portfolio selection problem is discussed. The model is a benchmark relative, mean-variance optimization problem in continuous time. In order to make the model computationally tractable, it is discretized in time and space. Thi ...
In this paper we consider a class of hybrid stochastic games with the piecewise open-loop information structure. These games are indexed over a parameter ε which represents the time scale ratio between the stochastic (jump process) and the dete ...
Society for Industrial and Applied Mathematics2008
We consider the problem of computing additively approximate Nash equilibria in non-cooperative two-player games. We provide a new polynomial time algorithm that achieves an approximation guarantee of 0.36392. Our work improves the previously best known (0. ...
Here, I review facts that are most probably known, namely that the information gain criterion used to drive experimental design in a linear-Gaussian model is submodular, so that a well-known approximation guarantee holds for the sequential greedy algorithm ...
We obtain a 1.5-approximation algorithm for the metric uncapacitated facility location problem (UFL), which improves on the previously best known 1.52-approximation algorithm by Mahdian, Ye and Zhang. Note, that the approximability lower bound by Guha and ...
This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Ha ...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse, we mean that only a few dictionary elements, compared to the ambient signal ...
This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Ha ...
We present a polynomial time approximation scheme for the real-time scheduling problem with fixed priorities when resource augmentation is allowed. For a fixed ε > 0, our algorithmcomputes an assignment using atmost (1+ε)·OPT +1 processors in polynomial ti ...
