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Synopsis
This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (IESC) in Corsica, France.
High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.
The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques andperspectives to analyze random phenomena.
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From the Back Cover
This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (IESC) in Corsica, France.
High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.
The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.
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High Dimensional Probability VII: The Cargèse Volume (Progress in Probability, 71)
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High Dimensional Probability VII: The Cargese Volume (Hardcover)
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Hardcover. Condition: new. Hardcover. This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783319405179
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High Dimensional Probability : The Cargèse Volume
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High Dimensional Probability VII: The Cargèse Volume (Progress in Probability, 71)
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High Dimensional Probability : The Cargèse Volume
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High Dimensional Probability VII: The Cargèse Volume (Progress in Probability, 71)
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High Dimensional Probability VII
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Springer International Publishing Sep 2016, 2016
ISBN 10: 3319405179
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (IESC) in Corsica, France.High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena. 492 pp. Englisch. Seller Inventory # 9783319405179
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High Dimensional Probability VII
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives a unique view on the mathematical methods used by experts to establish high dimensional resultsDisplays the wide scope of the types of problems to which these methods can be successfully appliedProvid. Seller Inventory # 122125818
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High Dimensional Probability
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Condition: New. Editor(s): Houdre, Christian; Rosinski, Jan; Mason, David. Series: Progress in Probability. Num Pages: 489 pages, biography. BIC Classification: PBT; PBU; PBV. Category: (G) General (US: Trade). Dimension: 235 x 155 x 27. Weight in Grams: 895. . 2016. Hardback. . . . . Seller Inventory # V9783319405179
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High Dimensional Probability VII
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Springer International Publishing, Springer Nature Switzerland Sep 2016, 2016
ISBN 10: 3319405179
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Buch. Condition: Neu. Neuware -This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (IESC) in Corsica, France.High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques andperspectives to analyze random phenomena.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 492 pp. Englisch. Seller Inventory # 9783319405179
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