Algorithms - ESA 2011

Outstanding text for graduate students and researchers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating

Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of

Since the 1970s, the Endangered Species Act (ESA), by virtue of its regulatory impact, has been a frequent subject of policy analysis. In this comprehensive history and critique of the ESA, Brian Cze

There are many books on data structures and algorithms, including some with useful libraries of C functions. Mastering Algorithms with C offers you a unique combination of theoretical background and w

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing in

The last few years have seen important advances in the use of genetic algorithms to address challenging optimization problems in industrial engineering. Genetic Algorithms and Engineering Design is th

"An Introduction to Distributed Algorithms" takes up some of the main concepts and algorithms, ranging from basic to advanced techniques and applications, that underlie the programming of distributed-

Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible i

This hypermedia CD-ROM provides an ideal format for the visual explanation of complex algorithms contained in the text Introduction to Algorithms, by Thomas H. Cormen, Charles E. Leiserson, and Ronal

This is an introduction to the field of efficient parallel algorithms and to the techniques for efficient parallelisation. It is self-contained and presumes no special knowledge of parallel computers or particular mathematics. The book emphasises designing algorithms within the timeless and abstracted context of a high-level programming language rather than within highly specific computer architectures. This is an approach which concentrates on the essence of algorithmic theory, determining and taking advantage of the inherently parallel nature of certain types of problem. The authors present regularly-used techniques and a range of algorithms which includes some of the more celebrated and well-known. Efficient Parallel Algorithms is targeted at non-specialists who are considering entering the field of parallel algorithms. It will be particularly useful for courses aimed at advanced undergraduate or new postgraduate students of computer science and mathematics.

There has been an explosive growth in the field of combinatorial algorithms. These algorithms depend not only on results in combinatorics and especially in graph theory, but also on the development of

In a world increasingly run by algorithms and artificial intelligence, Hatim Rahman traces how organizations are using algorithms to control workers in an "invisible cage." Inside the Invisible Cage uses unique longitudinal data to investigate how digital labor platforms use algorithms to dictate the actions of high-skilled workers by determining accepted behaviors, work opportunities, and even success. As Hatim Rahman explains, employers can use algorithms to shift rules and guidelines without notice, explanation, or recourse for workers. The invisible cage signals a profound shift in the way markets and organizations categorize and ultimately control people. Unlike previous forms of labor control, the invisible cage is ubiquitous, yet it is also opaque and shifting, which makes breaking free from it difficult for workers. This book traces how the invisible cage was developed over time and the implications it has for the spread of new technology, such as generative artificial intellig

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 set of two books can provides the basics for understanding how swarm intelligence algorithms work, together with their modifications and practical applications. It is useful for students studying

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramificatio

Algorithms are probably the most sophisticated tools that people have had at their disposal since the beginnings of human history. They have transformed science, industry, society. They upset the concepts of work, property, government, private life, even humanity. Going easily from one extreme to the other, we rejoice that they make life easier for us, but fear that they will enslave us. To get beyond this vision of good vs evil, this book takes a new look at our time, the age of algorithms. Creations of the human spirit, algorithms are what we made them. And they will be what we want them to be: it's up to us to choose the world we want to live in.

Algorithms are probably the most sophisticated tools that people have had at their disposal since the beginnings of human history. They have transformed science, industry, society. They upset the concepts of work, property, government, private life, even humanity. Going easily from one extreme to the other, we rejoice that they make life easier for us, but fear that they will enslave us. To get beyond this vision of good vs evil, this book takes a new look at our time, the age of algorithms. Creations of the human spirit, algorithms are what we made them. And they will be what we want them to be: it's up to us to choose the world we want to live in.

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to optimization with a focus on pr

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods,

From the critically acclaimed author Ausma Zehanat Khan, A Deadly Divide is the devastatingly powerful new thriller featuring beloved series detectives Esa Khattak and Rachel Getty.In the aftermath of a mass shooting at a mosque in Quebec, the local police apprehend Amadou Duchon—a young Muslim man at the scene helping the wounded—but release Etienne Roy, the local priest who was found with a weapon in his hands. The shooting looks like a hate crime, but detectives Esa Khattak and Rachel Getty sense there is more to the story. Sent to liaise with a community in the grip of fear, they find themselves in fraught new territory, fueled by the panic and suspicion exploited by a right-wing radio host.As Rachel and Esa grapple to stop tensions shutting the case down entirely, all the time, someone is pointing Esa in another direction, a shadowy presence who anticipates his every move.A Deadly Divide is a piercingly observed, gripping thriller that reveals the fractures that try to tear us all

This book presents a variety of widely used algorithms, expressing them in a pure functional programming language to make their structure and operation clearer to readers. In the opening chapter the a

The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek.We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execut

This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The a

This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finan

Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that

Learn how to build efficient, secure and robust code in C++ by using data structures and algorithms - the building blocks of C++Key FeaturesUse data structures such as arrays, stacks, trees, lists, an

This book covers all the relevant dictionary learning algorithms, presenting them in full detail and showing their distinct characteristics while also revealing the similarities. It gives implementati

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

This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approxi

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

This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based

The new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models.This book offers students and researchers a guide to dist

Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities. Logistics and transportation prob

This book includes introduction of several algorithms which are exclusively for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes th

This book takes a practical hands-on approach to developing low complexity algorithms and transforming them into working hardware. It follows a complete design approach – from algorithms to hardware a

Computer Vision: Principles, Algorithms, Applications, Learning (previously entitled Computer and Machine Vision) clearly and systematically presents the basic methodology of computer vision, covering