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2021 | OriginalPaper | Chapter

Non-lattice Covering and Quantization of High Dimensional Sets

Authors : Jack Noonan, Anatoly Zhigljavsky

Published in: Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

Publisher: Springer International Publishing

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Abstract

The main problem considered in this paper is construction and theoretical study of efficient n-point coverings of a d-dimensional cube [−1, 1]d. Targeted values of d are between 5 and 50; n can be in hundreds or thousands and the designs (collections of points) are nested. This paper is a continuation of our paper (Noonan and Zhigljavsky, SN Oper Res Forum, 2020), where we have theoretically investigated several simple schemes and numerically studied many more. In this paper, we extend the theoretical constructions of (Noonan and Zhigljavsky, SN Oper Res Forum, 2020) for studying the designs that were found to be superior to the ones theoretically investigated in (Noonan and Zhigljavsky, SN Oper Res Forum, 2020). We also extend our constructions for new construction schemes that provide even better coverings (in the class of nested designs) than the ones numerically found in (Noonan and Zhigljavsky, SN Oper Res Forum, 2020). In view of a close connection of the problem of quantization to the problem of covering, we extend our theoretical approximations and practical recommendations to the problem of construction of efficient quantization designs in a cube [−1, 1]d. In the last section, we discuss the problems of covering and quantization in a d-dimensional simplex; practical significance of this problem has been communicated to the authors by Professor Michael Vrahatis, a co-editor of the present volume.

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Footnotes
1
For simplicity of notation, vectors in \(\mathbb {R}^d\) are represented as rows.
 
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Metadata
Title
Non-lattice Covering and Quantization of High Dimensional Sets
Authors
Jack Noonan
Anatoly Zhigljavsky
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-66515-9_10

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