On solving large sparse linear systems arising from linear programming
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On solving large sparse linear systems arising from linear programming (2018)
DE PB NWISBN: 9783659763977 bzw. 3659763977, in Deutsch, LAP Lambert Academic Publishing Jul 2018, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Neuware - This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. 128 pp. Englisch, Books.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Neuware - This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. 128 pp. Englisch, Books.
2
On solving large sparse linear systems arising from linear programming
DE PB NWISBN: 9783659763977 bzw. 3659763977, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
On solving large sparse linear systems arising from linear programming: This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. Englisch, Taschenbuch.
On solving large sparse linear systems arising from linear programming: This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. Englisch, Taschenbuch.
3
On solving large sparse linear systems arising from linear programming
DE HC NWISBN: 9783659763977 bzw. 3659763977, in Deutsch, Lap Lambert Academic Publishing, gebundenes Buch, neu.
Lieferung aus: Deutschland, Versandkostenfrei innerhalb von Deutschland.
This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. Sofort lieferbar Lieferzeit 1-2 Werktage.
This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. Sofort lieferbar Lieferzeit 1-2 Werktage.
4
On solving large sparse linear systems arising from linear programming (2018)
DE PB NWISBN: 9783659763977 bzw. 3659763977, in Deutsch, 128 Seiten, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkosten nach: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, Syndikat Buchdienst, [4235284].
This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. 2018, Taschenbuch / Paperback, Neuware, H: 220mm, B: 150mm, 128, Internationaler Versand, Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung.
Von Händler/Antiquariat, Syndikat Buchdienst, [4235284].
This book in Computer Science is tailored towards solving the standard linear programming problem and the standard linear regression problem. First we p ose these problems as sequences of weighted linear systems We discuss a combination of a direct solver and an iterative solver for solving these sequences of weighted linear systems For this mixed solver approach a class of preconditioners based on low rank corrections is discussed and preconditioners constructed The choice of the low rank correction matrix is based on derived theoretical b ounds on the eigenvalues of the precondi toned matrix. In addition for linear programming we suggest a globally convergent in exact interior p oint algorithm Based on this algorithm we state a globally convergent mixed interior p oint algorithm that suits the class of preconditioners mentioned above. Furthermore for the case of linear regression we discuss another class of preconditioners based on downdating a constant factorized matrix at every iteration Also a new convex weighting function for linear regression is suggested and preconditioners based on this function discussed. 2018, Taschenbuch / Paperback, Neuware, H: 220mm, B: 150mm, 128, Internationaler Versand, Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung.
5
On solving large sparse linear systems arising from linear programming (2018)
EN PB NWISBN: 9783659763977 bzw. 3659763977, in Englisch, 128 Seiten, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandfertig in 4 - 5 Werktagen, Versandkostenfrei. Tatsächliche Versandkosten können abweichen.
Von Händler/Antiquariat, averdo24.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Von Händler/Antiquariat, averdo24.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
6
Symbolbild
On solving large sparse linear systems arising from linear programming
DE PB NWISBN: 9783659763977 bzw. 3659763977, in Deutsch, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, European-Media-Service Mannheim [1048135], Mannheim, Germany.
Publisher/Verlag: LAP Lambert Academic Publishing | Format: Paperback | Language/Sprache: english | 128 pp.
Von Händler/Antiquariat, European-Media-Service Mannheim [1048135], Mannheim, Germany.
Publisher/Verlag: LAP Lambert Academic Publishing | Format: Paperback | Language/Sprache: english | 128 pp.
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