Algorithms

With Iterative Learning Control Algorithms and Experimental Benchmarking the authors discuss the main methods of iterative learning control (ILC) and its interactions, as well as comparator performanc

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. Using these case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core.

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. Using these case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core.

Quantum computing explained in terms of elementary linear algebra, emphasizing computation and algorithms and requiring no background in physics.This introduction to quantum algorithms is concise but

This innovative book models pollution mitigation as a negative externality whilst also providing desirable and useful solutions, such as establishing the triangular equivalence relationship among the Lindahl equilibrium without transfers, the Nash bargaining solution with the payoffs of the Cournot-Nash equilibrium as the status quo point, and the social optimum under the Lindahl weights. By introducing programming algorithms to validate these relationships numerically, Zili Yang bridges the gap between analytical results and empirical modelling, ultimately solving the Lindahl equilibrium and hybrid Nash equilibria in the influential RICE model. This text demonstrates the complexity and variety of environment externality problems, ranging from mixed externality to correlated externalities to environmental externality under IRS and policy applications. Integrating theory, algorithms and applications in a comprehensive framework, The Environment and Externality will benefit scholars and

This innovative book models pollution mitigation as a negative externality whilst also providing desirable and useful solutions, such as establishing the triangular equivalence relationship among the Lindahl equilibrium without transfers, the Nash bargaining solution with the payoffs of the Cournot-Nash equilibrium as the status quo point, and the social optimum under the Lindahl weights. By introducing programming algorithms to validate these relationships numerically, Zili Yang bridges the gap between analytical results and empirical modelling, ultimately solving the Lindahl equilibrium and hybrid Nash equilibria in the influential RICE model. This text demonstrates the complexity and variety of environment externality problems, ranging from mixed externality to correlated externalities to environmental externality under IRS and policy applications. Integrating theory, algorithms and applications in a comprehensive framework, The Environment and Externality will benefit scholars and

Networks powered by algorithms are pervasive. Major contemporary technology trends - Internet of Things, Big Data, Digital Platform Power, Blockchain, and the Algorithmic Society - are manifestations of this phenomenon. The internet, which once seemed an unambiguous benefit to society, is now the basis for invasions of privacy, massive concentrations of power, and wide-scale manipulation. The algorithmic networked world poses deep questions about power, freedom, fairness, and human agency. The influential 1997 Federal Communications Commission whitepaper “Digital Tornado” hailed the “endless spiral of connectivity” that would transform society, and today, little remains untouched by digital connectivity. Yet fundamental questions remain unresolved, and even more serious challenges have emerged. This important collection, which offers a reckoning and a foretelling, features leading technology scholars who explain the legal, business, ethical, technical, and public policy challenges of b

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms conside

A successor to the first and second editions, this updated and revised book is a leading companion guide for students and engineers alike, specifically software engineers who design algorithms. While

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the au

Sparseness and heterogeneity of data are major challenges in the field of food science. Evolutionary algorithms can be effectively used to tackle these issues: in this book, we highlight some promisin

This book constitutes the refereed proceedings of the 16th International Workshop on Algorithms in Bioinformatics, WABI 2016, held in Aarhus, Denmark. The 25 full papers together with 2 invited talk

This book describes a variety of highly effective and efficient structure-preserving algorithms for second-order oscillatory differential equations. Such systems arise in many branches of science and

Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? Maybe you need a convenient source of relevant, current topics for a gradu

Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition ofAlgorithms in a Nutshell describes a large num

Opening with a detailed review of existing techniques for selective encryption, this text then examines algorithms that combine both encryption and compression. The book also presents a selection of s

Algorithmic design is not simply the use of computer to design architecture and objects. Algorithms allow designers to overcome the limitations of traditional CAD software and 3D modelers, reaching a

The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues. This book examines various aspects of the evaluation process with an emphasis on classification algorithms. The authors describe several techniques for classifier performance assessment, error estimation and resampling, obtaining statistical significance as well as selecting appropriate domains for evaluation. They also present a unified evaluation framework and highlight how different components of evaluation are both significantly interrelated and interdependent. The techniques presented in the book are illustrated using R and WEKA, facilitating better practical insight as well as implementation. Aimed at researchers in the theory and applications of machine learning, this book offers a solid basis for c

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible t

This comprehensive guide describes how evolutionary algorithms (EA) may be used to identify, model, and optimize day-to-day problems that arise for researchers in optimization and mobile networking. I

This easy-to-follow book provides a student-friendly introduction to programming and algorithms, using an active learning style in which deeper understanding is gained from evaluating, questioning and

High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, inclu

Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. T

Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book. The research reported demonstr

This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy

State-of-the-art analysis of geological structures has become increasingly quantitative but traditionally, graphical methods are used in teaching. This innovative lab book provides a unified methodology for problem-solving in structural geology using linear algebra and computation. Assuming only limited mathematical training, the book begins with classic orientation problems and progresses to more fundamental topics of stress, strain and error propagation. It introduces linear algebra methods as the foundation for understanding vectors and tensors, and demonstrates the application of geometry and kinematics in geoscience without requiring students to take a supplementary mathematics course. All algorithms are illustrated with a suite of online MATLAB functions, allowing users to modify the code to solve their own structural problems. Containing 20 worked examples and over 60 exercises, this is the ideal lab book for advanced undergraduates or beginning graduate students. It will also p

This book is devoted to studying algorithms for the solution of a class of quadratic matrix and vector equations. These equations appear, in different forms, in several practical applications, especia

Digital Video and HD: Algorithms and Interfaces provides a one-stop shop for the theory and engineering of digital video systems. Equally accessible to video engineers and those working in computer gr

Polyhedral functions provide a model for an important class of problems that includes both linear programming and applications in data analysis. General methods for minimizing such functions using the polyhedral geometry explicitly are developed. Such methods approach a minimum by moving from extreme point to extreme point along descending edges and are described generically as simplicial. The best-known member of this class is the simplex method of linear programming, but simplicial methods have found important applications in discrete approximation and statistics. The general approach considered in this text, first published in 2001, has permitted the development of finite algorithms for the rank regression problem. The key ideas are those of developing a general format for specifying the polyhedral function and the application of this to derive multiplier conditions to characterize optimality. Also considered is the application of the general approach to the development of active se

The field of graph algorithms has become one of the pillars of theoretical computer science. This is an introduction to graph algorithms accessible to anyone with a strong linear algebra background –

Kantardzic (computer engineering and science, U. of Louisville) offers students a single-volume introduction to the methods, tools, and algorithms in data mining that can also be used as a broad, if s

Written by prominent experts in the field, this monograph provides the first comprehensive, unified presentation of the structural, algorithmic and applied aspects of the theory of Boolean functions. The book focuses on algebraic representations of Boolean functions, especially disjunctive and conjunctive normal form representations. This framework looks at the fundamental elements of the theory (Boolean equations and satisfiability problems, prime implicants and associated short representations, dualization), an in-depth study of special classes of Boolean functions (quadratic, Horn, shellable, regular, threshold, read-once functions and their characterization by functional equations) and two fruitful generalizations of the concept of Boolean functions (partially defined functions and pseudo-Boolean functions). Several topics are presented here in book form for the first time. Because of the depth and breadth and its emphasis on algorithms and applications, this monograph will have sp

“Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in th

This book constitutes the refereed proceedings of the 7th International Workshop on Algorithms and Models for the Web-Graph, WAW 2010, held in Stanford, CA, USA, in December 2010, which was co-located

An updated, innovative approach to data structures and algorithms Written by an author team of experts in their fields, this authoritative guide demystifies even the most difficult mathematical concep

Multimedia processing demands efficient programming. This book shows you how to optimize data, singal, image, audio, speech, and video processing algorithms on embedded processors for real-time media

A culmination of the authors' years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational dat

This book discusses in detail all the relevant numerical methods for the classical N-body problem. It demonstrates how to develop clear and elegant algorithms for models of gravitational systems, and explains the fundamental mathematical tools needed to describe the dynamics of a large number of mutually attractive particles. Particular attention is given to the techniques needed to model astrophysical phenomena such as close encounters and the dynamics of black hole binaries. The author reviews relevant work in the field and covers applications to the problems of planetary formation and star cluster dynamics, both of Pleiades type and globular clusters. Self-contained and pedagogical, this book is suitable for graduate students and researchers in theoretical physics, astronomy and cosmology.

Using mathematical tools from number theory and finite fields, Applied Algebra: Codes, Ciphers, and Discrete Algorithms, Second Edition presents practical methods for solving problems in data security