Optimal algorithms for large sparse quadratic programming problems with uniformly bounded spectrum
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F06%3A00013637" target="_blank" >RIV/61989100:27240/06:00013637 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Optimal algorithms for large sparse quadratic programming problems with uniformly bounded spectrum
Original language description
Recently proposed algorithms for the solution of large quadratic programming problems are reviewed. An important feature of these algorithms is their capability to find an approximate solution of the convex equality and/or bound constrained quadratic programming problems with the uniformly bounded spectrum of the Hessian matrix at $O(1)$ iterations. If we consider a class of problems with the Hessian which is either sparse or can be expressed as a product of sparse matrices, then these algorithms can find the solution at the cost nearly proportional to the dimension of the problem. The theoretical results are presented and illustrated by numerical experiments.
Czech name
Optimální algoritmy pro rozsáhlé řídké problémy kvadratického programování
Czech description
V práci jou popsáný výsledky autora ve vývoji optimálních algoritmů pro rozsáhlé řídké problémy kvadratického programování
Classification
Type
C - Chapter in a specialist book
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA101%2F04%2F1145" target="_blank" >GA101/04/1145: Development and implementation of scalable numerical methods for solving physically realistic models of contact problems with friction in 2D and 3D</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Large-Scale Nonlinear Optimization Series: Nonconvex Optimization and Its Applications
ISBN
0-387-30063-5
Number of pages of the result
11
Pages from-to
83-93
Number of pages of the book
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Publisher name
Springer
Place of publication
Erice, Itálie
UT code for WoS chapter
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