Algorithms and error bounds for multivariate piecewise constant approximation [PDF]
, 2011 We review the surprisingly rich theory of approximation of functions of many vari- ables by piecewise constants. This covers for example the Sobolev-Poincar´e inequalities, parts of the theory of nonlinear approximation, Haar wavelets and tree ...
Davydov, Oleg
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Rational approximation of discrete data with asymptomatic behaviour [PDF]
This thesis is concerned with the least-squares approximation of discrete data that appear to exhibit asymptotic behaviour. In particular, we consider using rational functions as they are able to display a number of types of asymptotic behaviour.
Cooper, Philip
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Approximation algorithms and inapproximability of partition functions of spin systems [PDF]
, 2020 Over the past 30 years, the study of counting problems has become an interesting and important work. The framework of counting problems can capture applications in diverse fields, such as graph colouring and homomorphism in graph theory, and the Ising ...
Yang, Kuan
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Радіоелектронні і комп'ютерні системи, 2018 The problem of big data sets processing is considered. Efficiency of algorithms depends mainly on the appropriate mathematical tools. Now there exists a wide variety of different constructive tools for information analysis.
Iryna Victorivna Brysina +1 more
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Improved Multi-Pass Streaming Algorithms for Submodular Maximization with Matroid Constraints [PDF]
, 2020 We give improved multi-pass streaming algorithms for the problem of maximizing a monotone or arbitrary non-negative submodular function subject to a general p-matchoid constraint in the model in which elements of the ground set arrive one at a time in a ...
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020) +6 more
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Fuzzy and Tile Coding Approximation Techniques for Coevolution in Reinforcement Learning [PDF]
, 2005 This thesis investigates reinforcement learning algorithms suitable for learning in large state space problems and coevolution. In order to learn in large state spaces, the state space must be collapsed to a computationally feasible size and then ...
Laurissa Nadia Tokarchuk +1 more
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Simple Synchronous and Asynchronous Algorithms for Distributed Minimax Optimization
SICE Journal of Control, Measurement, and System Integration, 2017 Synchronous and asynchronous algorithms are presented for distributed minimax optimization. The objective here is to realize the minimization of the maximum of component functions over the standard multi-agent network, where each node of the network ...
Kenta Hanada +3 more
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A Performance Study of Some Approximation Algorithms for Computing a Small Dominating Set in a Graph [PDF]
, 2020 Article implements and tests the performances of several approximation algorithms for computing the minimum dominating set of a graph.
Potru, Rohan +5 more
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Local RBF approximation for scattered data fitting with bivariate splines [PDF]
, 2005 In this paper we continue our earlier research [4] aimed at developing effcient methods of local approximation suitable for the first stage of a spline based two-stage scattered data fitting algorithm.
Davydov, O., Sestini, A., Morandi, R.
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Improved approximation algorithms for optimization problems in graphs with superlogarithmic treewidth [PDF]
, 2003 In this paper we present two novel generic schemes for approximation algorithms for optimization to partial k-trees. Our first scheme yields deterministic polynomialtime algorithms achieving typically an approximation factor of k/ log n, where k
Chlebikova, Janka +14 more
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