Equivariant Stable Homotopy Theory and the Kervaire Invariant Problem PDF Download
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Author: Michael A. Hill
Publisher: Cambridge University Press
ISBN: 1108831443
Category : Mathematics
Languages : en
Pages : 881
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Book Description
A complete and definitive account of the authors' resolution of the Kervaire invariant problem in stable homotopy theory.
Author: Michael A. Hill
Publisher: Cambridge University Press
ISBN: 1108831443
Category : Mathematics
Languages : en
Pages : 881
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Book Description
A complete and definitive account of the authors' resolution of the Kervaire invariant problem in stable homotopy theory.
Author: Halsey Royden
Publisher: Pearson Modern Classics for Advanced Mathematics Series
ISBN: 9780134689494
Category : Functional analysis
Languages : en
Pages : 0
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Book Description
This text is designed for graduate-level courses in real analysis. Real Analysis, 4th Edition, covers the basic material that every graduate student should know in the classical theory of functions of a real variable, measure and integration theory, and some of the more important and elementary topics in general topology and normed linear space theory. This text assumes a general background in undergraduate mathematics and familiarity with the material covered in an undergraduate course on the fundamental concepts of analysis.
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ISBN:
Category : American literature
Languages : en
Pages : 2092
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Book Description
Author: László Erdős
Publisher: American Mathematical Soc.
ISBN: 1470436485
Category : Mathematics
Languages : en
Pages : 239
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Book Description
A co-publication of the AMS and the Courant Institute of Mathematical Sciences at New York University This book is a concise and self-contained introduction of recent techniques to prove local spectral universality for large random matrices. Random matrix theory is a fast expanding research area, and this book mainly focuses on the methods that the authors participated in developing over the past few years. Many other interesting topics are not included, and neither are several new developments within the framework of these methods. The authors have chosen instead to present key concepts that they believe are the core of these methods and should be relevant for future applications. They keep technicalities to a minimum to make the book accessible to graduate students. With this in mind, they include in this book the basic notions and tools for high-dimensional analysis, such as large deviation, entropy, Dirichlet form, and the logarithmic Sobolev inequality. This manuscript has been developed and continuously improved over the last five years. The authors have taught this material in several regular graduate courses at Harvard, Munich, and Vienna, in addition to various summer schools and short courses. Titles in this series are co-published with the Courant Institute of Mathematical Sciences at New York University.
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Category : Engineering
Languages : en
Pages : 1554
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Book Description
Author: Steven Lord
Publisher: Walter de Gruyter
ISBN: 311026255X
Category : Mathematics
Languages : en
Pages : 468
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Book Description
This book is the first complete study and monograph dedicated to singular traces. The text mathematically formalises the study of traces in a self contained theory of functional analysis. Extensive notes will treat the historical development. The final section will contain the most complete and concise treatment known of the integration half of Connes' quantum calculus. Singular traces are traces on ideals of compact operators that vanish on the subideal of finite rank operators. Singular traces feature in A. Connes' interpretation of noncommutative residues. Particularly the Dixmier trace,which generalises the restricted Adler-Manin-Wodzicki residue of pseudo-differential operators and plays the role of the residue for a new catalogue of 'geometric' spaces, including Connes-Chamseddine standard models, Yang-Mills action for quantum differential forms, fractals, isospectral deformations, foliations and noncommutative index theory. The theory of singular traces has been studied after Connes' application to non-commutative geometry and physics by various authors. Recent work by Nigel Kalton and the authors has advanced the theory of singular traces.Singular traces can be equated to symmetric functionals of symmetric sequence or function spaces, residues of zeta functions and heat kernel asymptotics, and characterised by Lidksii and Fredholm formulas. The traces and formulas used in noncommutative geometry are now completely understood in this theory, with surprising new mathematical and physical consequences. For mathematical readers the text offers fundamental functional analysis results and, due to Nigel Kalton's contribution, a now complete theory of traces on compact operators. For mathematical physicists and other users of Connes' noncommutative geometry the text offers a complete reference to Dixmier traces and access to the deeper mathematical features of traces on ideals associated to the harmonic sequence. These features, not known and not discussed in general texts on noncommutative geometry, are undoubtably physical and probe to the fascinating heart of classical limits and quantization.
Author: Robert F. Tichy
Publisher: Springer Science & Business Media
ISBN: 3211742808
Category : Mathematics
Languages : en
Pages : 416
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Book Description
This volume contains 21 research and survey papers on recent developments in the field of diophantine approximation, which are based on lectures given at a conference at the Erwin Schrödinger-Institute (Vienna, 2003). The articles are either in the spirit of more classical diophantine analysis or of a geometric or combinatorial flavor. Several articles deal with estimates for the number of solutions of diophantine equations as well as with congruences and polynomials.
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Category : Associations, institutions, etc
Languages : en
Pages : 1380
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Book Description
1981- in 2 v.: v.1, Subject index; v.2, Title index, Publisher/title index, Association name index, Acronym index, Key to publishers' and distributors' abbreviations.
Author: Stephen Boyd
Publisher: SIAM
ISBN: 9781611970777
Category : Mathematics
Languages : en
Pages : 203
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Book Description
In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.
Author: Giuseppe Bonaccorso
Publisher: Packt Publishing Ltd
ISBN: 1785884514
Category : Computers
Languages : en
Pages : 352
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Book Description
Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.
