The Concentration of Measure Phenomenon - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Concentration of Measure Phenomenon write by Michel Ledoux. This book was released on 2001. The Concentration of Measure Phenomenon available in PDF, EPUB and Kindle. The observation of the concentration of measure phenomenon is inspired by isoperimetric inequalities. This book offers the basic techniques and examples of the concentration of measure phenomenon. It presents concentration functions and inequalities, isoperimetric and functional examples, spectrum and topological applications and product measures.
Concentration Inequalities
Concentration Inequalities - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Concentration Inequalities write by Stéphane Boucheron. This book was released on 2013-02-07. Concentration Inequalities available in PDF, EPUB and Kindle. Describes the interplay between the probabilistic structure (independence) and a variety of tools ranging from functional inequalities to transportation arguments to information theory. Applications to the study of empirical processes, random projections, random matrix theory, and threshold phenomena are also presented.
Concentration of Measure Inequalities in Information Theory, Communications, and Coding
Concentration of Measure Inequalities in Information Theory, Communications, and Coding - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Concentration of Measure Inequalities in Information Theory, Communications, and Coding write by Maxim Raginsky. This book was released on 2014. Concentration of Measure Inequalities in Information Theory, Communications, and Coding available in PDF, EPUB and Kindle. Concentration of Measure Inequalities in Information Theory, Communications, and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding.
Probability in Banach Spaces
Probability in Banach Spaces - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Probability in Banach Spaces write by Michel Ledoux. This book was released on 2013-03-09. Probability in Banach Spaces available in PDF, EPUB and Kindle. Isoperimetric, measure concentration and random process techniques appear at the basis of the modern understanding of Probability in Banach spaces. Based on these tools, the book presents a complete treatment of the main aspects of Probability in Banach spaces (integrability and limit theorems for vector valued random variables, boundedness and continuity of random processes) and of some of their links to Geometry of Banach spaces (via the type and cotype properties). Its purpose is to present some of the main aspects of this theory, from the foundations to the most important achievements. The main features of the investigation are the systematic use of isoperimetry and concentration of measure and abstract random process techniques (entropy and majorizing measures). Examples of these probabilistic tools and ideas to classical Banach space theory are further developed.
Concentration of Measure for the Analysis of Randomized Algorithms
Concentration of Measure for the Analysis of Randomized Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Concentration of Measure for the Analysis of Randomized Algorithms write by Devdatt P. Dubhashi. This book was released on 2009-06-15. Concentration of Measure for the Analysis of Randomized Algorithms available in PDF, EPUB and Kindle. Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff–Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff–Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians.
