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Sampling in Combinatorial and Geometric Set Systems
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.
Multidimensional Residue Theory and Applications
Residue theory is an active area of complex analysis with connections and applications to fields as diverse as partial differential and integral equations, computer algebra, arithmetic or diophantine geometry, and mathematical physics. Multidimensional Residue Theory and Applications defines and studies multidimensional residues via analytic continuation for holomorphic bundle-valued current maps. This point of view offers versatility and flexibility to the tools and constructions proposed, allowing these residues to be defined and studied outside the classical case of complete intersection. The book goes on to show how these residues are algebraic in nature, and how they relate and apply to...
Iwasawa Theory and Its Perspective, Volume 1
Iwasawa theory began in the late 1950s with a series of papers by Kenkichi Iwasawa on ideal class groups in the cyclotomic tower of number fields and their relation to $p$-adic $L$-functions. The theory was later generalized by putting it in the context of elliptic curves and modular forms. The main motivation for writing this book was the need for a total perspective of Iwasawa theory that includes the new trends of generalized Iwasawa theory. Another motivation of this book is an update of the classical theory for class groups taking into account the changed point of view on Iwasawa theory. The goal of this first part of the two-part publication is to explain the theory of ideal class groups, including its algebraic aspect (the Iwasawa class number formula), its analytic aspect (Leopoldt–Kubota $L$-functions), and the Iwasawa main conjecture, which is a bridge between the algebraic and the analytic aspects. The second part of the book will be published as a separate volume in the same series, Mathematical Surveys and Monographs of the American Mathematical Society.
Data Depth
The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University. The workshop brought together researchers from two different communities: statisticians and specialists in computational geometry. The main idea unifying these two research areas turned out to be the notion of data depth, which is an important notion both in statistics and in the study of efficiency of algorithms used in computational geometry. Many of the articles in the book lay down the foundations for further collaboration and interdisciplinary research. Information for our distributors: Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with the Association for Computer Machinery (ACM).
Characterization of Probability Distributions on Locally Compact Abelian Groups
It is well known that if two independent identically distributed random variables are Gaussian, then their sum and difference are also independent. It turns out that only Gaussian random variables have such property. This statement, known as the famous Kac-Bernstein theorem, is a typical example of a so-called characterization theorem. Characterization theorems in mathematical statistics are statements in which the description of possible distributions of random variables follows from properties of some functions of these random variables. The first results in this area are associated with famous 20th century mathematicians such as G. Pólya, M. Kac, S. N. Bernstein, and Yu. V. Linnik. By no...
Chips Challenging Champions
One of the earliest dreams of the fledgling field of artificial intelligence (AI) was to build computer programs that could play games as well as or better than the best human players. Despite early optimism in the field, the challenge proved to be surprisingly difficult. However, the 1990s saw amazing progress. Computers are now better than humans in checkers, Othello and Scrabble; are at least as good as the best humans in backgammon and chess; and are rapidly improving at hex, go, poker, and shogi. This book documents the progress made in computers playing games and puzzles. The book is the definitive source for material of high-performance game-playing programs.
Amenability of Discrete Groups by Examples
The main topic of the book is amenable groups, i.e., groups on which there exist invariant finitely additive measures. It was discovered that the existence or non-existence of amenability is responsible for many interesting phenomena such as, e.g., the Banach-Tarski Paradox about breaking a sphere into two spheres of the same radius. Since then, amenability has been actively studied and a number of different approaches resulted in many examples of amenable and non-amenable groups. In the book, the author puts together main approaches to study amenability. A novel feature of the book is that the exposition of the material starts with examples which introduce a method rather than illustrating it. This allows the reader to quickly move on to meaningful material without learning and remembering a lot of additional definitions and preparatory results; those are presented after analyzing the main examples. The techniques that are used for proving amenability in this book are mainly a combination of analytic and probabilistic tools with geometric group theory.
STACS 2006
This book constitutes the refereed proceedings of the 23rd Annual Symposium on Theoretical Aspects of Computer Science, held in February 2006. The 54 revised full papers presented together with three invited papers were carefully reviewed and selected from 283 submissions. The papers address the whole range of theoretical computer science including algorithms and data structures, automata and formal languages, complexity theory, semantics, and logic in computer science.
Algorithms - ESA 2003
This book constitutes the refereed proceedings of the 11th Annual European Symposium on Algorithms, ESA 2003, held in Budapest, Hungary, in September 2003. The 66 revised full papers presented were carefully reviewed and selected from 165 submissions. The scope of the papers spans the entire range of algorithmics from design and mathematical analysis issues to real-world applications, engineering, and experimental analysis of algorithms.
Algorithm Theory - SWAT 2004
This volume contains the papers presented at SWAT 2004, the 9th Scandi- vian Workshop on Algorithm Theory, which was held on July 8-10, 2004, at the Louisiana Museum of Modern Art in Humlebæk on the Øresund coast north of Copenhagen. The SWAT workshop, in reality a full-?edged conference, has been held biennially since 1988 and rotates among the ?ve Nordic countries, D- mark, Finland, Iceland, Norway, and Sweden. The previous meetings took place ? in Halmstad (1988), Bergen (1990), Helsinki (1992), Arhus (1994), Reykjavik (1996), Stockholm (1998), Bergen (2000), and Turku (2002). SWAT alternates with the Workshop on Algorithms and Data Structures (WADS), held in o- numbered years. Thecallf...
