Results 11 to 20 of about 1,062,165 (308)
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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Approximate approximation on a quantum annealer [PDF]
Proceedings of the 17th ACM International Conference on Computing Frontiers, 2020 Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes. Quantum annealers (QA) are physical devices that aim at this class of problems by exploiting quantum mechanical properties of nature.
Irmi Sax +5 more
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Variational inequations and approximation [PDF]
, 1974 The existence and uniqueness of the solution of a variational inequality is considered, and methods of approximation of the solution are given.
Noor, MA
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An Approximation Algorithm for Approximation Rank [PDF]
2009 24th Annual IEEE Conference on Computational Complexity, 2009 One of the strongest techniques available for showing lower bounds on quantum communication complexity is the logarithm of the approximation rank of the communication matrix--the minimum rank of a matrix which is entrywise close to the communication matrix.
Troy Lee, Adi Shraibman
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An approximation method using approximate approximations [PDF]
Applicable Analysis, 2006 The aim of this article is to extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials.
Frank Müller, Werner Varnhorn
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Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, 2022 For a function $g\colon\{0,1\}^m\to\{0,1\}$, a function $f\colon \{0,1\}^n\to\{0,1\}$ is called a $g$-polymorphism if their actions commute: $f(g(\mathsf{row}_1(Z)),\ldots,g(\mathsf{row}_n(Z))) = g(f(\mathsf{col}_1(Z)),\ldots,f(\mathsf{col}_m(Z)))$ for all $Z\in\{0,1\}^{n\times m}$.
Chase, Gilad +4 more
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Approximating Approximate Pattern Matching
CoRR, 2018 ISSN:1868 ...
Jan Studený, Przemyslaw Uznanski
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Approximate Clustering without the Approximation [PDF]
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009 Approximation algorithms for clustering points in metric spaces is a flourishing area of research, with much research effort spent on getting a better understanding of the approximation guarantees possible for many objective functions such as k-median, k-means, and min-sum clustering. This quest for better approximation algorithms is further fueled by
Maria-Florina Balcan +2 more
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Estimates of the Approximation Error Using Rademacher Complexity: Learning Vector-Valued Functions [PDF]
, 2008 For certain families of multivariable vector-valued functions to be approximated, the accuracy of approximation schemes made up of linear combinations of computational units containing adjustable parameters is investigated.
Gnecco Giorgio +7 more
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Approximating Approximate Distance Oracles
CoRR, 2016 Given a finite metric space $(V,d)$, an approximate distance oracle is a data structure which, when queried on two points $u,v \in V$, returns an approximation to the the actual distance between $u$ and $v$ which is within some bounded stretch factor of the true distance.
Michael Dinitz, Zeyu Zhang 0003
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