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109
Approximability and Parameterized Complexity of Minmax Values
"... We consider approximating the minmax value of a multiplayer game in strategic form. Tightening recent bounds by Borgs et al., we observe that approximating the value with a precision of ɛ log n digits (for any constant ɛ > 0) is NPhard, where n is the size of the game. On the other hand, appro ..."
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Cited by 2 (0 self)
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, approximating the value with a precision of c log log n digits (for any constant c ≥ 1) can be done in quasipolynomial time. We consider the parameterized complexity of the problem, with the parameter being the number of pure strategies k of the player for which the minmax value is computed. We show
Regression Methods for Pricing Complex AmericanStyle Options
 IEEE Transactions on Neural Networks
, 2000
"... We introduce and analyze a simulationbased, approximate dynamic programming method for pricing complex Americanstyle options, with a possibly highdimensional underlying state space. We work within a finitely parameterized family of approximate value functions, and introduce a variant of value ite ..."
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Cited by 157 (3 self)
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We introduce and analyze a simulationbased, approximate dynamic programming method for pricing complex Americanstyle options, with a possibly highdimensional underlying state space. We work within a finitely parameterized family of approximate value functions, and introduce a variant of value
The parameterized complexity of global constraints
 In Proceedings of AAAI 2008, AAAI Conference on Artificial Intelligence
, 2008
"... We argue that parameterized complexity is a useful tool with which to study global constraints. In particular, we show that many global constraints which are intractable to propagate completely have natural parameters which make them fixedparameter tractable and which are easy to compute. This tract ..."
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Cited by 16 (4 self)
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. For instance, we prove that value symmetry is fixedparameter tractable to break in the number of symmetries. Finally, we argue that parameterized complexity can be used to derive results about the approximability of constraint propagation.
Strong computational lower bounds via parameterized complexity
, 2006
"... We develop new techniques for deriving strong computational lower bounds for a class of wellknown NPhard problems. This class includes weighted satisfiability, dominating set, hitting set, set cover, clique, and independent set. For example, although a trivial enumeration can easily test in time O ..."
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Cited by 39 (5 self)
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O(n k) if a given graph of n vertices has a clique of size k, we prove that unless an unlikely collapse occurs in parameterized complexity theory, the problem is not solvable in time f(k)n o(k) for any function f, even if we restrict the parameter values to be bounded by an arbitrarily small
In Search of an Optimal Parameterization of Curves
"... Approximation of curves by parametric polynomials or rational curves needs a linkage between curve points and parameter values. The quality of the approximation is highly dependent on this a priori parameterization. This quality criterium can be measured when the curve is given by dense or continuou ..."
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Approximation of curves by parametric polynomials or rational curves needs a linkage between curve points and parameter values. The quality of the approximation is highly dependent on this a priori parameterization. This quality criterium can be measured when the curve is given by dense
The Complexity of PolynomialTime Approximation
 TO APPEAR IN JOURNAL THEORY OF COMPUTING SYSTEMS
, 2006
"... In 1996, Khanna and Motwani [KM96] proposed three logicbased optimization problems constrained by planar structure, and offered the hypothesis that these putatively fundamental problems might provide insight into characterizing the class of optimization problems that admit a polynomialtime approxi ..."
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Cited by 6 (0 self)
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time approximation scheme (PTAS). The main contribution of this paper is to explore this program from the point of view of parameterized complexity. Problems of optimization are naturally parameterized by the parameter k = 1/ɛ. An optimization problem admits a PTAS if and only if there is an algorithm Φ, that, given
Parameterized Weighted Containment
"... Abstract. Partiallyspecified systems and specifications are used in formal methods such as stepwise design and query checking. The goal of these methods is to explore the design or refine it by examining possible completions of the missing information. Existing methods consider a setting in which t ..."
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Cited by 1 (1 self)
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reasoning. Technically, every transition in a weighted automaton A has a cost, and the value A assigns to a finite word w is the sum of the costs on the transitions participating in the most expensive accepting run of A on w. We study parameterized weighted containment: given three weighted automata A, B
www.elsevier.com/locate/pocean Modelling planktonic ecosystems: parameterizing complexity
"... This paper explores several simplified representations of complexity or ecological ‘texture ’ in models of the marine planktonic ecosystem. It is relatively straightforward to formulate more complex models to include explicitly different functional groups of phytoplankton, zooplankton and bacteria, ..."
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. Moreover, ecosystem models often become unstable for small changes in parameter values, and increasing complexity may not lead to increased stability. Here we consider alternative formulations for ecosystem models that try to represent complex interactions, such as the microbial loop, in simpler, less
Regression Methods for Pricing Complex
"... We introduce and analyze a simulationbased approximate dynamic programming method for pricing complex Americanstyle options, with a possibly highdimensional underlying state space. We work within a finitely parameterized family of approximate value functions, and introduce a variant of value iter ..."
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We introduce and analyze a simulationbased approximate dynamic programming method for pricing complex Americanstyle options, with a possibly highdimensional underlying state space. We work within a finitely parameterized family of approximate value functions, and introduce a variant of value
Results 1  10
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109