On the complexity of computing the \(L_q\) norm

DOI10.1016/j.jco.2018.07.001zbMath1415.65033OpenAlexW2862910548MaRDI QIDQ1791678

Stefan Heinrich

Publication date: 11 October 2018

Published in: Journal of Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jco.2018.07.001

zbMATH Keywords

complexityapproximationdeterministic and randomized algorithmnorm computation

Mathematics Subject Classification ID

Algorithms for approximation of functions (65D15) Complexity and performance of numerical algorithms (65Y20) Randomized algorithms (68W20)

Related Items (5)

Sampling discretization and related problems ⋮ Randomized complexity of parametric integration and the role of adaption. I: Finite dimensional case ⋮ Algorithms and complexity for functions on general domains ⋮ Solvable integration problems and optimal sample size selection ⋮ Sampling discretization error of integral norms for function classes

Cites Work

• The randomized complexity of indefinite integration
• Randomized approximation of Sobolev embeddings. II
• Randomized approximation of Sobolev embeddings. III
• Function spaces in Lipschitz domains and optimal rates of convergence for sampling
• Tractability of multivariate problems. Volume I: Linear information
• Deterministic and stochastic error bounds in numerical analysis
• The real number model in numerical analysis
• Some nonlinear problems are as easy as the approximation problem
• Monte Carlo approximation of weakly singular integral operators
• The randomized information complexity of elliptic PDE
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