Submodularity and Randomized rounding techniques for Optimal Experimental Design

DOI10.1016/j.endm.2010.05.086zbMath1237.93057OpenAlexW2072277757MaRDI QIDQ2883636

Stéphane Gaubert, Mustapha Bouhtou, Guillaume Sagnol

Publication date: 13 May 2012

Published in: Electronic Notes in Discrete Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.endm.2010.05.086

zbMATH Keywords

discrete optimization\(D\)-optimalityoptimal design of experimentsKiefer's \(p\)-criterionpolynomial-time approximability

Mathematics Subject Classification ID

Design techniques (robust design, computer-aided design, etc.) (93B51) Computer aspects of numerical algorithms (65Y99)

Related Items (11)

Competitive online algorithms for resource allocation over the positive semidefinite cone ⋮ Computing optimal designs of multiresponse experiments reduces to second-order cone program\-ming ⋮ Near-optimal discrete optimization for experimental design: a regret minimization approach ⋮ Parallelized maximization of nonsubmodular function subject to a cardinality constraint ⋮ Parallelized maximization of nonsubmodular function subject to a cardinality constraint ⋮ Polynomial-Time Algorithms for Multiple-Arm Identification with Full-Bandit Feedback ⋮ Approximation Algorithms for D-optimal Design ⋮ A branch-and-bound algorithm for the exact optimal experimental design problem ⋮ Ascent with quadratic assistance for the construction of exact experimental designs ⋮ Randomized Parallel Algorithm for Maximizing Nonsubmodular Function Subject to Cardinality Constraint ⋮ Gaussian Process Landmarking on Manifolds

Uses Software

• NetQuest

Cites Work

• Unnamed Item
• Unnamed Item
• Improving updating rules in multiplicative algorithms for computing \(D\)-optimal designs
• On linear regression designs which maximize information
• Pipage rounding: a new method of constructing algorithms with proven performance guarantee
• D-optimal design of a monitoring network for parameter estimation of distributed systems
• Sequences converging to D-optimal designs of experiments
• Optimal design: Variation in structure and performance under change of criterion
• An analysis of approximations for maximizing submodular set functions—I
• Maximizing a Submodular Set Function Subject to a Matroid Constraint (Extended Abstract)

This page was built for publication: Submodularity and Randomized rounding techniques for Optimal Experimental Design