Stoc 11 Proceedings Of The 43rd Acm Symposium On Theory Of Computing
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Computing And Combinatorics
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Author : Donghyun Kim
language : en
Publisher: Springer Nature
Release Date : 2020-08-27
Computing And Combinatorics written by Donghyun Kim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-27 with Computers categories.
This book constitutes the proceedings of the 26th International Conference on Computing and Combinatorics, COCOON 2020, held in Atlanta, GA, USA, in August 2020. Due to the COVID-19 pandemic COCOON 2020 was organized as a fully online conference. The 54 papers presented in this volume were carefully reviewed and selected from 126 submissions. The papers cover various topics, including algorithm design, approximation algorithm, graph theory, complexity theory, problem solving, optimization, computational biology, computational learning, communication network, logic, and game theory.
Stoc 11
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Author : Association for Computing Machinery. Special Interest Group for Automata and Computability Theory
language : en
Publisher:
Release Date : 2011
Stoc 11 written by Association for Computing Machinery. Special Interest Group for Automata and Computability Theory and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Algorithmic Game Theory
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Author : Tobias Harks
language : en
Publisher: Springer Nature
Release Date : 2020-09-08
Algorithmic Game Theory written by Tobias Harks and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-08 with Computers categories.
This book constitutes the refereed proceedings of the 13th International Symposium on Algorithmic Game Theory, SAGT 2020, held in Augsburg, Germany, in September 2020.* The 21 full papers presented together with 3 abstract papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: auctions and mechanism design, congestion games and flows over time, markets and matchings, scheduling and games on graphs, and social choice and cooperative games. * The conference was held virtually due to the COVID-19 pandemic.
Secure System Design And Trustable Computing
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Author : Chip-Hong Chang
language : en
Publisher: Springer
Release Date : 2015-09-17
Secure System Design And Trustable Computing written by Chip-Hong Chang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-17 with Technology & Engineering categories.
This book provides the foundations for understanding hardware security and trust, which have become major concerns for national security over the past decade. Coverage includes issues related to security and trust in a variety of electronic devices and systems related to the security of hardware, firmware and software, spanning system applications, online transactions and networking services. This serves as an invaluable reference to the state-of-the-art research that is of critical significance to the security of and trust in, modern society’s microelectronic-supported infrastructures.
Tractability
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Author : Lucas Bordeaux
language : en
Publisher: Cambridge University Press
Release Date : 2014-02-06
Tractability written by Lucas Bordeaux and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-06 with Computers categories.
Classical computer science textbooks tell us that some problems are 'hard'. Yet many areas, from machine learning and computer vision to theorem proving and software verification, have defined their own set of tools for effectively solving complex problems. Tractability provides an overview of these different techniques, and of the fundamental concepts and properties used to tame intractability. This book will help you understand what to do when facing a hard computational problem. Can the problem be modelled by convex, or submodular functions? Will the instances arising in practice be of low treewidth, or exhibit another specific graph structure that makes them easy? Is it acceptable to use scalable, but approximate algorithms? A wide range of approaches is presented through self-contained chapters written by authoritative researchers on each topic. As a reference on a core problem in computer science, this book will appeal to theoreticians and practitioners alike.
Sampling In Combinatorial And Geometric Set Systems
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Author : Nabil H. Mustafa
language : en
Publisher: American Mathematical Society
Release Date : 2022-01-14
Sampling In Combinatorial And Geometric Set Systems written by Nabil H. Mustafa and has been published by American Mathematical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-14 with Mathematics categories.
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.
Stoc 11
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Author : STOC
language : en
Publisher:
Release Date : 2011
Stoc 11 written by STOC and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computer science categories.
Alice And Bob Meet Banach
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Author : Guillaume Aubrun
language : en
Publisher: American Mathematical Society
Release Date : 2024-07-29
Alice And Bob Meet Banach written by Guillaume Aubrun and has been published by American Mathematical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-29 with Mathematics categories.
The quest to build a quantum computer is arguably one of the major scientific and technological challenges of the twenty-first century, and quantum information theory (QIT) provides the mathematical framework for that quest. Over the last dozen or so years, it has become clear that quantum information theory is closely linked to geometric functional analysis (Banach space theory, operator spaces, high-dimensional probability), a field also known as asymptotic geometric analysis (AGA). In a nutshell, asymptotic geometric analysis investigates quantitative properties of convex sets, or other geometric structures, and their approximate symmetries as the dimension becomes large. This makes it especially relevant to quantum theory, where systems consisting of just a few particles naturally lead to models whose dimension is in the thousands, or even in the billions. Alice and Bob Meet Banach is aimed at multiple audiences connected through their interest in the interface of QIT and AGA: at quantum information researchers who want to learn AGA or apply its tools; at mathematicians interested in learning QIT, or at least the part of QIT that is relevant to functional analysis/convex geometry/random matrix theory and related areas; and at beginning researchers in either field. Moreover, this user-friendly book contains numerous tables and explicit estimates, with reasonable constants when possible, which make it a useful reference even for established mathematicians generally familiar with the subject.
Parameterized Algorithmics For Network Analysis Clustering Querying
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Author : Christian Komusiewicz
language : en
Publisher: Univerlagtuberlin
Release Date : 2011
Parameterized Algorithmics For Network Analysis Clustering Querying written by Christian Komusiewicz and has been published by Univerlagtuberlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Statistical Implications Of Turing S Formula
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Author : Zhiyi Zhang
language : en
Publisher: John Wiley & Sons
Release Date : 2016-10-14
Statistical Implications Of Turing S Formula written by Zhiyi Zhang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-14 with Mathematics categories.
Features a broad introduction to recent research on Turing’s formula and presents modern applications in statistics, probability, information theory, and other areas of modern data science Turing's formula is, perhaps, the only known method for estimating the underlying distributional characteristics beyond the range of observed data without making any parametric or semiparametric assumptions. This book presents a clear introduction to Turing’s formula and its connections to statistics. Topics with relevance to a variety of different fields of study are included such as information theory; statistics; probability; computer science inclusive of artificial intelligence and machine learning; big data; biology; ecology; and genetics. The author provides examinations of many core statistical issues within modern data science from Turing's perspective. A systematic approach to long-standing problems such as entropy and mutual information estimation, diversity index estimation, domains of attraction on general alphabets, and tail probability estimation is presented in light of the most up-to-date understanding of Turing's formula. Featuring numerous exercises and examples throughout, the author provides a summary of the known properties of Turing's formula and explains how and when it works well; discusses the approach derived from Turing's formula in order to estimate a variety of quantities, all of which mainly come from information theory, but are also important for machine learning and for ecological applications; and uses Turing's formula to estimate certain heavy-tailed distributions. In summary, this book: • Features a unified and broad presentation of Turing’s formula, including its connections to statistics, probability, information theory, and other areas of modern data science • Provides a presentation on the statistical estimation of information theoretic quantities • Demonstrates the estimation problems of several statistical functions from Turing's perspective such as Simpson's indices, Shannon's entropy, general diversity indices, mutual information, and Kullback–Leibler divergence • Includes numerous exercises and examples throughout with a fundamental perspective on the key results of Turing’s formula Statistical Implications of Turing's Formula is an ideal reference for researchers and practitioners who need a review of the many critical statistical issues of modern data science. This book is also an appropriate learning resource for biologists, ecologists, and geneticists who are involved with the concept of diversity and its estimation and can be used as a textbook for graduate courses in mathematics, probability, statistics, computer science, artificial intelligence, machine learning, big data, and information theory. Zhiyi Zhang, PhD, is Professor of Mathematics and Statistics at The University of North Carolina at Charlotte. He is an active consultant in both industry and government on a wide range of statistical issues, and his current research interests include Turing's formula and its statistical implications; probability and statistics on countable alphabets; nonparametric estimation of entropy and mutual information; tail probability and biodiversity indices; and applications involving extracting statistical information from low-frequency data space. He earned his PhD in Statistics from Rutgers University.