Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 251 pages. 9.75x7.00x0.75 inches. In Stock.
Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Lingua: Inglese
Editore: MP-AMM American Mathematical, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Lingua: Inglese
Editore: American Mathematical Society, Providence, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Paperback. Condizione: new. Paperback. Understanding the behavior of basic sampling techniques and intrinsic geometric attributes of data is an invaluable skill that is in high demand for both graduate students and researchers in mathematics, machine learning, and theoretical computer science. The last ten years have seen significant progress in this area, with many open problems having been resolved during this time. These include optimal lower bounds for epsilon-nets for many geometric set systems, the use of shallow-cell complexity to unify proofs, simpler and more efficient algorithms, and the use of epsilon-approximations for construction of coresets, to name a few. This book presents a thorough treatment of these probabilistic, combinatorial, and geometric methods, as well as their combinatorial and algorithmic applications. It also revisits classical results, but with new and more elegant proofs. While mathematical maturity will certainly help in appreciating the ideas presented here, only a basic familiarity with discrete mathematics, probability, and combinatorics is required to understand the material. Presents a thorough treatment of these probabilistic, combinatorial, and geometric methods, as well as their combinatorial and algorithmic applications. The book also revisits classical results, but with new and more elegant proofs. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: American Mathematical Society, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: American Mathematical Society, Providence, 2022
ISBN 10: 1470461560 ISBN 13: 9781470461560
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EUR 214,61
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Understanding the behavior of basic sampling techniques and intrinsic geometric attributes of data is an invaluable skill that is in high demand for both graduate students and researchers in mathematics, machine learning, and theoretical computer science. The last ten years have seen significant progress in this area, with many open problems having been resolved during this time. These include optimal lower bounds for epsilon-nets for many geometric set systems, the use of shallow-cell complexity to unify proofs, simpler and more efficient algorithms, and the use of epsilon-approximations for construction of coresets, to name a few. This book presents a thorough treatment of these probabilistic, combinatorial, and geometric methods, as well as their combinatorial and algorithmic applications. It also revisits classical results, but with new and more elegant proofs. While mathematical maturity will certainly help in appreciating the ideas presented here, only a basic familiarity with discrete mathematics, probability, and combinatorics is required to understand the material. Presents a thorough treatment of these probabilistic, combinatorial, and geometric methods, as well as their combinatorial and algorithmic applications. The book also revisits classical results, but with new and more elegant proofs. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.