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Journal ArticleDOI

Sphere Packings, Lattices and Groups

Werner Fischer, +1 more
- 01 Feb 1990 - 
- Vol. 191, pp 286-286
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This article is published in Zeitschrift Fur Kristallographie.The article was published on 1990-02-01. It has received 1584 citations till now. The article focuses on the topics: Atomic packing factor & Sphere packing.

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Citations
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MonographDOI

Planning Algorithms: Introductory Material

TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Book

A Probabilistic Theory of Pattern Recognition

TL;DR: The Bayes Error and Vapnik-Chervonenkis theory are applied as guide for empirical classifier selection on the basis of explicit specification and explicit enforcement of the maximum likelihood principle.
Journal ArticleDOI

Unsupervised learning of finite mixture models

TL;DR: The novelty of the approach is that it does not use a model selection criterion to choose one among a set of preestimated candidate models; instead, it seamlessly integrate estimation and model selection in a single algorithm.
Journal ArticleDOI

Closest point search in lattices

TL;DR: An efficient closest point search algorithm, based on the Schnorr-Euchner (1995) variation of the Pohst (1981) method, is implemented and is shown to be substantially faster than other known methods.
Journal ArticleDOI

Quantization

TL;DR: The key to a successful quantization is the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.
References
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MonographDOI

Planning Algorithms: Introductory Material

TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Book

A Probabilistic Theory of Pattern Recognition

TL;DR: The Bayes Error and Vapnik-Chervonenkis theory are applied as guide for empirical classifier selection on the basis of explicit specification and explicit enforcement of the maximum likelihood principle.
Journal ArticleDOI

Unsupervised learning of finite mixture models

TL;DR: The novelty of the approach is that it does not use a model selection criterion to choose one among a set of preestimated candidate models; instead, it seamlessly integrate estimation and model selection in a single algorithm.
Journal ArticleDOI

Closest point search in lattices

TL;DR: An efficient closest point search algorithm, based on the Schnorr-Euchner (1995) variation of the Pohst (1981) method, is implemented and is shown to be substantially faster than other known methods.
BookDOI

Handbook of global optimization

TL;DR: This paper presents algorithms for global optimization of mixed-integer nonlinear programs using the Reformulation-Linearization/Convexification Technique (RLT) and an introduction to dynamical search.