A Computer Experiment Oriented Approach to Algorithmic Complexity: Computer Applications of Statistics - Brossura
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This book forms the much needed strong interface between algorithmic complexity and computer experiments using a careful blending of traditional ideas in algorithms with untraditional research in computer experiments (esp. fitting stochastic models to non-random data). While establishing the aforesaid interface, the important role of statistical bounds and their empirical estimates obtained over a finite range (called empirical O) is discovered as a bonus. While these bounds are very valuable for the average case, our research suggests in addition that there is no need to be over-conservative in the worst case just as the statistical bounds safeguard against making tall optimistic claims for the best cases. In short the statistical bounds have a sense of "calculated guarantee" that is neither too risky nor too conservative. In parallel computing, with every change of the processor, it can be argued that it is the weight of the operation that changes. Hence, if the bound is itself based on weights, it should be deemed as the ideal one.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Dr. Soubhik Chakraborty is a Reader, Deptt. of Applied Mathematics, BIT Mesra, Ranchi, India with 50 international papers, an ACM and IEEE Reviewer (Comp. Rev./Trans. Comp.). Dr. Suman Kumar Sourabh is a Sr. Faculty, Deptt. of Statistics and Computer Applications, T. M. Bhagalpur University, Bhagalpur, India with 10 international papers.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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A Computer Experiment Oriented Approach to Algorithmic Complexity
Editore:
LAP LAMBERT Academic Publishing Jun 2010, 2010
ISBN 10: 3838377435
ISBN 13: 9783838377438
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book forms the much needed strong interface between algorithmic complexity and computer experiments using a careful blending of traditional ideas in algorithms with untraditional research in computer experiments (esp. fitting stochastic models to non-random data). While establishing the aforesaid interface, the important role of statistical bounds and their empirical estimates obtained over a finite range (called empirical O) is discovered as a bonus. While these bounds are very valuable for the average case, our research suggests in addition that there is no need to be over-conservative in the worst case just as the statistical bounds safeguard against making tall optimistic claims for the best cases. In short the statistical bounds have a sense of 'calculated guarantee' that is neither too risky nor too conservative. In parallel computing, with every change of the processor, it can be argued that it is the weight of the operation that changes. Hence, if the bound is itself based on weights, it should be deemed as the ideal one. 192 pp. Englisch. Codice articolo 9783838377438
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A Computer Experiment Oriented Approach to Algorithmic Complexity
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838377435
ISBN 13: 9783838377438
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Da: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chakraborty SoubhikDr. Soubhik Chakraborty is a Reader, Deptt. of Applied Mathematics, BIT Mesra, Ranchi, India with 50 international papers, an ACM and IEEE Reviewer (Comp. Rev./Trans. Comp.). Dr. Suman Kumar Sourabh is a Sr. Facu. Codice articolo 5418030
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A Computer Experiment Oriented Approach to Algorithmic Complexity
Editore:
LAP LAMBERT Academic Publishing Jun 2010, 2010
ISBN 10: 3838377435
ISBN 13: 9783838377438
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -This book forms the much needed strong interface between algorithmic complexity and computer experiments using a careful blending of traditional ideas in algorithms with untraditional research in computer experiments (esp. fitting stochastic models to non-random data). While establishing the aforesaid interface, the important role of statistical bounds and their empirical estimates obtained over a finite range (called empirical O) is discovered as a bonus. While these bounds are very valuable for the average case, our research suggests in addition that there is no need to be over-conservative in the worst case just as the statistical bounds safeguard against making tall optimistic claims for the best cases. In short the statistical bounds have a sense of 'calculated guarantee' that is neither too risky nor too conservative. In parallel computing, with every change of the processor, it can be argued that it is the weight of the operation that changes. Hence, if the bound is itself based on weights, it should be deemed as the ideal one.Books on Demand GmbH, Überseering 33, 22297 Hamburg 192 pp. Englisch. Codice articolo 9783838377438
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A Computer Experiment Oriented Approach to Algorithmic Complexity : Computer Applications of Statistics
Editore:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838377435
ISBN 13: 9783838377438
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book forms the much needed strong interface between algorithmic complexity and computer experiments using a careful blending of traditional ideas in algorithms with untraditional research in computer experiments (esp. fitting stochastic models to non-random data). While establishing the aforesaid interface, the important role of statistical bounds and their empirical estimates obtained over a finite range (called empirical O) is discovered as a bonus. While these bounds are very valuable for the average case, our research suggests in addition that there is no need to be over-conservative in the worst case just as the statistical bounds safeguard against making tall optimistic claims for the best cases. In short the statistical bounds have a sense of 'calculated guarantee' that is neither too risky nor too conservative. In parallel computing, with every change of the processor, it can be argued that it is the weight of the operation that changes. Hence, if the bound is itself based on weights, it should be deemed as the ideal one. Codice articolo 9783838377438
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A Computer Experiment Oriented Approach to Algorithmic Complexity: Computer Applications of Statistics
Editore:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838377435
ISBN 13: 9783838377438
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