26,99 € *

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If you know how to program with Python and also know a little about probability, you&#8217;re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you&#8217;ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book&#8217;s computational approach helps you get a solid start. * Use your existing programming skills to learn and understand Bayesian statistics * Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing * Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey * Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.

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2.589,99 € *

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This dynamic reference work provides solutions to vital algorithmic problems for scholars, researchers, practitioners, teachers and students in fields such as computer science, mathematics, statistics, biology, economics, financial software, and medical informatics. This second edition is broadly expanded, building upon the success of its former edition with more than 450 new and updated entries. These entries are designed to ensure algorithms are presented from growing areas of research such as bioinformatics, combinatorial group testing, differential privacy, enumeration algorithms, game theory, massive data algorithms, modern learning theory, social networks, and VLSI CAD algorithms. Over 630 entries are organized alphabetically by problem, with subentries allowing for distinct solutions. Each entry includes a description of the basic algorithmic problem; the input and output specifications; key results; examples of applications; citations to key literature, open problems, experimental results, links to data sets and downloadable code. All entries are peer-reviewed, written by leading experts in the field&#8212;and each entry contains links to a summary of the author&#8217;s research work. This defining reference is available in both print and online&#8212;a dynamic living work with hyperlinks to related entries, cross references citations, and a myriad other valuable URLs. New and Updated entries include: Algorithmic Aspects of Distributed Sensor Networks, Algorithms for Modern Computers Bioinformatics Certified Reconstruction and Mesh Generation Combinatorial Group Testing Compression of Text and Data Structures Computational Counting Computational Economics Computational Geometry Differential Privacy Enumeration Algorithms Exact Exponential Algorithms Game Theory Graph Drawing Group Testing Internet Algorithms Kernels and Compressions Massive Data Algorithms Mathematical Optimization Modern Learning Theory Social Networks Stable Marriage Problems, k-SAT Algorithms Sublinear Algorithms Tile Self-Assembly VLSI CAD Algorithms

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106,99 € *

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Constraint satisfaction problems are a central pillar of modern computational complexity theory. This monograph provides an introduction to the rapidly growing field of Quantum Hamiltonian Complexity (QHC), which includes the study of quantum constraint satisfaction problems. Over the past decade and a half, this field has witnessed fundamental breakthroughs, ranging from the establishment of a Quantum Cook-Levin Theorem to deep insights into the structure of 1D low-temperature quantum systems via so-called area laws. Quantum Hamiltonian Complexity provides the reader with a computer science-oriented introduction to the subject in order to help bridge the language barrier between computer scientists and physicists in the field. As such, it includes the following: (1) The motivations and history of the field, (2) a glossary of condensed matter physics terms explained in computer-science friendly language, (3) overviews of central ideas from condensed matter physics, such as indistinguishable particles, mean field theory, tensor networks, and area laws, and (4) brief expositions of selected computer science-based results in the area. For example, as part of the latter, it provides a novel information theoretic presentation of Bravyi's polynomial time algorithm for Quantum 2-SAT. Quantum Hamiltonian Complexity reviews some of the most fundamental results in QHC and is an ideal reference for computer scientists with little or no background in quantum information.

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76,99 € *

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The NP-completeness of SAT is a celebrated example of the power of bounded-depth computation: the core of the argument is a depth reduction establishing that any small nondeterministic circuit - an arbitrary NP computation on an arbitrary input - can be simulated by a small non deterministic circuit of depth 2 with unbounded fan-in - a SAT instance. Many other examples permeate theoretical computer science. On the Power of Small-Depth Computation discusses a selected subset of them, and includes a few unpublished proofs. On the Power of Small-Depth Computation starts with a unified treatment of the challenge of exhibiting explicit functions that have small correlation with low-degree polynomials over . It goes on to describe an unpublished proof that small bounded-depth circuits (AC°) have exponentially small correlation with the parity function. The proof is due to Adam Klivans and Salil Vadhan; it builds upon and simplifies previous ones. Thereafter, it looks at a depth-reduction result by Leslie Valiant, the proof of which has not before appeared in full. It concludes by presenting the result by Benny Applebaum, Yuval Ishai, and Eyal Kushilevitz that shows that, under standard complexity theoretic assumptions, many cryptographic primitives can be implemented in very restricted computational models. On the Power of Small-Depth Computation is an ideal primer for anyone with an interest in computational complexity, random structures and algorithms and theoretical computer science generally.

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175,99 € *

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Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research. This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages. This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.

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192,00 € *

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Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research. This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages. This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.

Anbieter: Thalia AT

Stand: 29.03.2020 Zum Angebot

Stand: 29.03.2020 Zum Angebot