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Approximation and Online Algorithms
This book constitutes revised selected papers from the thoroughly refereed workshop proceedings of the 20th International Workshop on Approximation and Online Algorithms, WAOA 2022, which was colocated with ALGO 2022 and took place in Potsdam, Germany, in September 2022.The 12 papers included in these proceedings were carefully reviewed and selected from21 submissions. They focus on topics such as graph algorithms, network design, algorithmic game theory, approximation and online algorithms, etc.
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Index Structures for Data Warehouses
Data warehouses differ significantly from traditional transaction-oriented operational database applications. Indexing techniques and index structures applied in the transaction-oriented context are not feasible for data warehouses.This work develops specific heuristic indexing techniques which process range queries on aggregated data more efficiently than those traditionally used in transaction-oriented systems. The book presents chapters on:- the state of the art in data warehouse research- data storage and index structures- finding optimal tree-based index structures- aggregated data in tree-based index structures- performance models for tree-based index structures- and techniques for comparing index structures.
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Efficient Algorithms
"E?ziente Algorithmen" was the title of the ?rst book by Kurt Mehlhorn in 1977. It was meant as a text for graduate students and published in German by Teubner-Verlag. We decided to adopt this title 32 years later for this Festschrift in honor of Kurt on the occasion of his 60th birthday. It contains contributions by his former PhD students, many of whom are now university teachers themselves, and colleagues with whom he cooperated closely within his career. It is our pleasure that even Kurt's former PhD advisor, Bob Constable from Cornell University,kindlyagreedtocontribute.Manyofthecontributionswerepresented at a colloquium held in Kurt's honor on August 27 and 28, 2009 in Saarbrucken, Germany. This Festschriftshowsclearlyhowthe ?eld ofalgorithmicshas developedand matured in the decades since Kurt wrote his book with the same title. The classic approach based on discrete mathematics and computability and complexity theory continues to be the foundation of the ?eld with ever new and important challenges as the ?rst chapters of this Festschrift show. Kurt has contributed signi?cantly to classical algorithmics and gained worldwide repu- tion.Starting from research in computability theory in his PhD thesis he made major contributions to complexity theory, graph algorithms, data structures, and was one of the ?rst to recognize the signi?cance of computational geometry contributing one of the early textbooks on the subject.
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Approximation Algorithms
Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.
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Algorithms for Data and Computation Privacy
This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book.Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook–Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world.This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.
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Automatic Generation Of Algorithms
In the rapidly evolving domain of computational problem-solving, this book delves into the cutting-edge Automatic Generation of Algorithms (AGA) paradigm, a groundbreaking approach poised to redefine algorithm design for optimization problems. Spanning combinatorial optimization, machine learning, genetic programming, and beyond, it investigates AGA's transformative capabilities across diverse application areas. The book initiates by introducing fundamental combinatorial optimization concepts and NPhardness significance, laying the foundation for understanding AGA's necessity and potential. It then scrutinizes the pivotal Master Problem concept in AGA and the art of modeling for algorithm generation. The exploration progresses with integrating genetic programming and synergizing AGA with evolutionary computing. Subsequent chapters delve into the AGA-machine learning intersection, highlighting their shared optimization foundation while contrasting divergent objectives. The automatic generation of metaheuristics is examined, aiming to develop versatile algorithmic frameworks adaptable to various optimization problems. Furthermore, the book explores applying reinforcement learning techniques to automatic algorithm generation. Throughout, it invites readers to reimagine algorithmic design boundaries, offering insights into AGA's conceptual underpinnings, practical applications, and future directions, serving as an invitation for researchers, practitioners, and enthusiasts in computer science, operations research, artificial intelligence, and beyond to embark on a journey toward computational excellence where algorithms are born, evolved, and adapted to meet ever-changing real-world problem landscapes.
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Algorithms in Algebraic Geometry
In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its Applications on September 2006 is one tangible indication of the interest. This volume of articles captures some of the spirit of the IMA workshop.
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Optimal Analysis of Structures by Concepts of Symmetry and Regularity
Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The value of the presented methods becomes all the more evident in cases where the analysis needs to be repeated hundreds or even thousands of times, as for the optimal design of structures by different metaheuristic algorithms. The book is of interest to anyone engaged in computer-aided analysis and design and software developers in this field. Though the methods are demonstrated mainly through skeletal structures, continuum models have also been added to show the generality of the methods. The concepts presented are not only applicable to different types of structures but can also be used for the analysis of other systems such as hydraulic and electrical networks.
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Wireless Algorithms, Systems, and Applications
The three-volume set constitutes the proceedings of the 17th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2022, which was held during October 28-30, 2022. The conference took place in Dalian, China.The 95 full and 62 short papers presented in these proceedings were carefully reviewed and selected from 265 submissions. The contributions in theoretical frameworks and analysis of fundamental cross-layer protocol and network design and performance issues; distributed and localized algorithm design and analysis; information and coding theory for wireless networks; localization; mobility models and mobile social networking; underwater and underground networks; vehicular networks; algorithms, systems, and applications of edge computing
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Structural and Functional Aspects of Biocomputing Systems for Data Processing
Due to the diversity of contexts in which biological computation is performed, a major problem is the selection of functional-oriented techniques for the analysis of biological sequences in a huge environment. The performances of various sequences in biocomputational algorithms are evaluated with variant features to prove their efficiency in real-time environments.Structural and Functional Aspects of Biocomputing Systems for Data Processing provides insight into the structural and functional aspects of biological sequences and the pattern recognition they embed into the data processingcepts, methodologies, and empirical research advances of various biological data mining systems through machine learning approaches. Covering topics such as DNA sequencing, high-speed architecture, and medical image processing, this premier reference source is an essential resource for healthcare professionals, biological systems in biocomputing systems. It extends recent con specialists, industrial professionals, PCR testing professionals, scientists, bioinformaticians, students and educators of higher education, librarians, researchers, and academicians.
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Discrete Structures
Discrete Structures introduces readers to the mathematical structures and methods that form the foundation of computer science and features multiple techniques that readers will turn to regularly throughout their careers in computer and information sciences.Over the course of five modules, students learn specific skills including binary and modular arithmetic, set notation, methods of counting, evaluating sums, and solving recurrences. They study the basics of probability, proof by induction, growth of functions, and analysis techniques. The book also discusses general problem-solving techniques that are widely applicable to real problems. Each module includes motivation applications, technique, theory, and further opportunities for application.Informed by extensive experience teaching in computer science programs, Discrete Structures has been developed specifically for first-year students in those programs. The material is also suitable for courses in computer engineering, as well as those for students who are transferring from other disciplines and just beginning their computer science or engineering education.
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Bistatic SAR Data Processing Algorithms
Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so signal processing is more challenging. Focusing on imaging aspects of bistatic SAR signal processing, this book covers resolution analysis, echo generation methods, imaging algorithms, imaging parameter estimation, and motion compensation methods. The book is ideal for researchers and engineers in SAR signal and data processing, as well as those working in bistatic and multistatic radar imaging, and in the radar sciences. Graduate students with a background in radar who are interested in bistatic and multistatic radar will find this book a helpful reference. Gives a general and updated framework for image formation using signal processing aspectsStarts with an introduction to traditional SAR before moving on to more advanced topicsOffers readers a range of exhaustive tools to process signals and form imagesProvides a solid reference for the imaging of other complicated SARSample image synthesis exercises are available from the book's companion site
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Mathematics of Discrete Structures for Computer Science
Mathematics plays a key role in computer science, some researchers would consider computers as nothing but the physical embodiment of mathematical systems. And whether you are designing a digital circuit, a computer program or a new programming language, you need mathematics to be able to reason about the design -- its correctness, robustness and dependability. This book covers the foundational mathematics necessary for courses in computer science.The common approach to presenting mathematical concepts and operators is to define them in terms of properties they satisfy, and then based on these definitions develop ways of computing the result of applying the operators and prove them correct. This book is mainly written for computer science students, so here the author takes a different approach: he starts by defining ways of calculating the results of applying the operators and then proves that they satisfy various properties. After justifying his underlying approach the author offers detailed chapters covering propositional logic, predicate calculus, sets, relations, discrete structures, structured types, numbers, and reasoning about programs.The book contains chapter and section summaries, detailed proofs and many end-of-section exercises -- key to the learning process. The book is suitable for undergraduate and graduate students, and although the treatment focuses on areas with frequent applications in computer science, the book is also suitable for students of mathematics and engineering.
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WALCOM: Algorithms and Computation
This book constitutes the proceedings of the 11th International Workshop on Algorithms and Computation, WALCOM 2017, held in Hsinchu, Taiwan, in March 2017.The 35 full papers presented together with three invited talks were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on invited talks; computational geometry; combinatorial optimization; graph drawing; graph algorithms; space-efficient algorithms; computational complexity; approximation algorithms.
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Wireless Algorithms, Systems, and Applications
The two-volume set LNCS 12385 + 12386 constitutes the proceedings of the 15th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2020, which was held during September 13-15, 2020. The conference was planned to take place in Qingdao, China; due to the COVID-19 pandemic it was held virtually. The 67 full and 14 short papers presented in these proceedings were carefully reviewed and selected from 216 submissions. These submissions cover many hot research topics, including machine-learning algorithms for wireless systems and applications, Internet of Things (IoTs) and related wireless solutions, wireless networking for cyber-physical systems (CPSs), security and privacy solutions for wireless applications, blockchain solutions for mobile applications, mobile edge computing, wireless sensor networks, distributed and localized algorithm design and analysis, wireless crowdsourcing, mobile cloud computing, vehicular networks, wireless solutions for smart cities, wireless algorithms for smart grids, mobile social networks, mobile system security, storage systems for mobile applications, etc.
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Algorithms for Sensor Systems
This book constitutes revised selected papers from the 13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017, held in Vienna, in September 2017.The 17 full papers presented in this volume were carefully reviewed and selected from 30 submissions. ALGOSENSORS is an international symposium dedicated to the algorithmic aspects of wireless networks. Originally focused on sensor networks, it now covers algorithmic issues arising in wireless networks of all types of computational entities, static or mobile, including sensor networks, sensor-actuator networks, autonomous robots. The focus is on the design and analysis of algorithms, models of computation, and experimental analysis.
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Computation of Biomolecular Structures
Computational techniques have become an indispensable part of Molecular Biology, Biochemistry, and Molecular Design. In conjunction with refined experimental methods and powerful hardware, they enable us to analyze and visualize biomolecular structures, simulate their motions and to a variable degree understand their physicochemical properties and function. In addition, they provide essentially the only way to analyze and correlate the astronomical amounts of experimental sequence and structural data accumulating in international databases. We have good reasons to believe that further advances in this area will eventually enable us to predict with sufficient accuracy many structural and functional properties of fairly large biomolecules, given their sequence and specified environmental conditions. However, it is also important to realize that in achieving this goal, we encounter several serious problems of conceptual and methodological nature, the solution of which requires new approaches and algorithms. For example, we need better force fields, more efficient optimization routines, an adequate description of electrostatics and hydration, reliable methods to compute free energies, and ways to extent the length of molecular dynamics simulations by several orders of magnitude.
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Recent Advances in Harmony Search Algorithm
Nowadays, music-inspired phenomenon-mimicking harmony search algorithm is fast growing with many applications. One of key success factors of the algorithm is the employment of a novel stochastic derivative which can be used even for discrete variables. Instead of traditional calculus-based gradient, the algorithm utilizes musician’s experience as a derivative in searching for an optimal solution. This can be a new paradigm and main reason in the successes of various applications.The goal of this book is to introduce major advances of the harmony search algorithm in recent years. The book contains 14 chapters with the following subjects: State-of-the-art in the harmony search algorithm structure; robotics (robot terrain and manipulator trajectory); visual tracking; web text data mining; power flow planning; fuzzy control system; hybridization (with Taguchi method or SQP method); groundwater management; irrigation ; logistics; timetabling; and bioinformatics (RNA structure prediction).This book collects the above-mentioned theory and applications, which are dispersed in various technical publications, so that readers can have a good grasp of current status of the harmony search algorithm and foster new breakthroughs in their fields using the algorithm.
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Parallel Processing and Parallel Algorithms
Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.
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Random Discrete Structures
The articles in this volume present the state of the art in a variety of areas of discrete probability, including random walks on finite and infinite graphs, random trees, renewal sequences, Stein's method for normal approximation and Kohonen-type self-organizing maps. This volume also focuses on discrete probability and its connections with the theory of algorithms. Classical topics in discrete mathematics are represented as are expositions that condense and make readable some recent work on Markov chains, potential theory and the second moment method. This volume is suitable for mathematicians and students.
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Concurrent Programming: Algorithms, Principles, and Foundations
This book is devoted to the most difficult part of concurrent programming, namely synchronization concepts, techniques and principles when the cooperating entities are asynchronous, communicate through a shared memory, and may experience failures. Synchronization is no longer a set of tricks but, due to research results in recent decades, it relies today on sane scientific foundations as explained in this book.In this book the author explains synchronization and the implementation of concurrent objects, presenting in a uniform and comprehensive way the major theoretical and practical results of the past 30 years. Among the key features of the book are a new look at lock-based synchronization (mutual exclusion, semaphores, monitors, path expressions); an introduction to the atomicity consistency criterion and its properties and a specific chapter on transactional memory; an introduction to mutex-freedom and associated progress conditions such as obstruction-freedom and wait-freedom; a presentation of Lamport's hierarchy of safe, regular and atomic registers and associated wait-free constructions; a description of numerous wait-free constructions of concurrent objects (queues, stacks, weak counters, snapshot objects, renaming objects, etc.); a presentation of the computability power of concurrent objects including the notions of universal construction, consensus number and the associated Herlihy's hierarchy; and a survey of failure detector-based constructions of consensus objects. The book is suitable for advanced undergraduate students and graduate students in computer science or computer engineering, graduate students in mathematics interested in the foundations of process synchronization, and practitioners and engineers who need to produce correct concurrent software. The reader should have a basic knowledge of algorithms and operating systems.
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Algorithms for Next Generation Networks
Data networking now plays a major role in everyday life and new applications continue to appear at a blinding pace. Yet we still do not have a sound foundation for designing, evaluating and managing these networks.This book covers topics at the intersection of algorithms and networking. It builds a complete picture of the current state of research on Next Generation Networks and the challenges for the years ahead. Particular focus is given to evolving research initiatives and the architecture they propose and implications for networking.Topics: Network design and provisioning, hardware issues, layer-3 algorithms and MPLS, BGP and Inter AS routing, packet processing for routing, security and network management, load balancing, oblivious routing and stochastic algorithms, network coding for multicast, overlay routing for P2P networking and content delivery.This timely volume will be of interest to a broad readership from graduate students to researchers looking to survey recent research its open questions.
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Link Mining: Models, Algorithms, and Applications
With the recent ?ourishing research activities on Web search and mining, social networkanalysis,informationnetworkanalysis,informationretrieval,linkana- sis,andstructuraldatamining,researchonlinkmininghasbeenrapidlygrowing, forminganew?eldofdatamining. Traditionaldataminingfocuseson"?at"or"isolated"datainwhicheachdata objectisrepresentedasanindependentattributevector. However,manyreal-world data sets are inter-connected, much richer in structure, involving objects of h- erogeneoustypesandcomplexlinks. Hence,thestudyoflinkminingwillhavea highimpactonvariousimportantapplicationssuchasWebandtextmining,social networkanalysis,collaborative?ltering,andbioinformatics. Asanemergingresearch?eld,therearecurrentlynobooksfocusingonthetheory andtechniquesaswellastherelatedapplicationsforlinkmining,especiallyfrom aninterdisciplinarypointofview. Ontheotherhand,duetothehighpopularity oflinkagedata,extensiveapplicationsrangingfromgovernmentalorganizationsto commercial businesses to people's daily life call for exploring the techniques of mininglinkagedata.Therefore,researchersandpractitionersneedacomprehensive booktosystematicallystudy,furtherdevelop,andapplythelinkminingtechniques totheseapplications. Thisbookcontainscontributedchaptersfromavarietyofprominentresearchers inthe?eld. Whilethechaptersarewrittenbydifferentresearchers,thetopicsand contentareorganizedinsuchawayastopresentthemostimportantmodels,al- rithms,andapplicationsonlinkmininginastructuredandconciseway. Giventhe lackofstructurallyorganizedinformationonthetopicoflinkmining,thebookwill provideinsightswhicharenoteasilyaccessibleotherwise. Wehopethatthebook willprovideausefulreferencetonotonlyresearchers,professors,andadvanced levelstudentsincomputersciencebutalsopractitionersinindustry. Wewouldliketoconveyourappreciationtoallauthorsfortheirvaluablec- tributions. WewouldalsoliketoacknowledgethatthisworkissupportedbyNSF throughgrantsIIS-0905215,IIS-0914934,andDBI-0960443. Chicago,Illinois PhilipS. Yu Urbana-Champaign,Illinois JiaweiHan Pittsburgh,Pennsylvania ChristosFaloutsos v Contents Part I Link-Based Clustering 1 Machine Learning Approaches to Link-Based Clustering...3 Zhongfei(Mark)Zhang,BoLong,ZhenGuo,TianbingXu, andPhilipS.Yu 2 Scalable Link-Based Similarity Computation and Clustering...45 XiaoxinYin,JiaweiHan,andPhilipS. Yu 3 Community Evolution and Change Point Detection in Time-Evolving Graphs...73 JimengSun,SpirosPapadimitriou,PhilipS. Yu,andChristosFaloutsos Part II Graph Mining and Community Analysis 4 A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks...107 GalileoMarkNamata,HossamSharara,andLiseGetoor 5 Markov Logic: A Language and Algorithms for Link Mining...135 PedroDomingos,DanielLowd,StanleyKok,AniruddhNath,Hoifung Poon,MatthewRichardson,andParagSingla 6 Understanding Group Structures and Properties in Social Media...163 LeiTangandHuanLiu 7 Time Sensitive Ranking with Application to Publication Search...187 XinLi,BingLiu,andPhilipS. Yu 8 Proximity Tracking on
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From Algorithms to Thinking Machines
This book introduces and provides an analysis of the basic concepts of algorithms, data, and computation and discusses the role of algorithms in ruling and shaping our world. It provides a clear understanding of the power and impact on humanity of the pervasive use of algorithms.From Algorithms to Thinking Machines combines a layman's approach with a well-founded scientific description to discuss both principles and applications of algorithms, Big Data, and machine intelligence. The book provides a clear and deep description of algorithms, software systems, data-driven applications, machine learning, and data science concepts, as well as the evolution and impact of artificial intelligence.After introducing computing concepts, the book examines the relationships between algorithms and human work, discussing how jobs are being affected and how computers and software programs are influencing human life and the labor sphere. Topics such as value alignment, collective intelligence, Big Data impact, automatic decision methods, social control, and political uses of algorithms are illustrated and discussed at length without excessive technical detail. Issues related to how corporations, governments, and autocratic regimes are exploiting algorithms and machine intelligence methods to influence people, laws, and markets are extensively addressed. Ethics principles in software programming and human value insertion into artificial intelligence algorithms are also discussed.
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Evolutionary Algorithms
This IMA Volume in Mathematics and its Applications EVOLUTIONARY ALGORITHMS is based on the proceedings of a workshop that was an integral part of the 1996-97 IMA program on "MATHEMATICS IN HIGH-PERFORMANCE COMPUTING." I thank Lawrence David Davis (Tica Associates), Kenneth De Jong (Computer Science, George Mason University), Michael D. Vose (Computer Science, The University of Tennessee), and L. Darrell Whitley (Computer Science, Colorado State University) for their excellent work in organizing the workshop and for editing the proceedings. Further appreciation is ex tended to Donald G. Truhlar (Chemistry and Supercomputing Institute, University of Minnesota) who was also one of the workshop organizers. In addition, I also take this opportunity to thank the National Science Foundation (NSF), Minnesota Supercomputing Institute (MSI), and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr., Professor and Director v PREFACE The IMA Workshop on Evolutionary Algorithms brought together many of the top researchers working in the area of Evolutionary Com putation for a week of intensive interaction. The field of Evolutionary Computation has developed significantly over the past 30 years and today consists a variety of subfields such as genetic algorithms, evolution strate gies, evolutionary programming, and genetic programming, each with their own algorithmic perspectives and goals.
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Advances in Algorithms, Languages, and Complexity
This book contains a collection of survey papers in the areas of algorithms, lan guages and complexity, the three areas in which Professor Ronald V. Book has made significant contributions. As a fonner student and a co-author who have been influenced by him directly, we would like to dedicate this book to Professor Ronald V. Book to honor and celebrate his sixtieth birthday. Professor Book initiated his brilliant academic career in 1958, graduating from Grinnell College with a Bachelor of Arts degree. He obtained a Master of Arts in Teaching degree in 1960 and a Master of Arts degree in 1964 both from Wesleyan University, and a Doctor of Philosophy degree from Harvard University in 1969, under the guidance of Professor Sheila A. Greibach. Professor Book's research in discrete mathematics and theoretical com puter science is reflected in more than 150 scientific publications. These works have made a strong impact on the development of several areas of theoretical computer science. A more detailed summary of his scientific research appears in this volume separately.
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125 Problems in Text Algorithms
String matching is one of the oldest algorithmic techniques, yet still one of the most pervasive in computer science. The past 20 years have seen technological leaps in applications as diverse as information retrieval and compression. This copiously illustrated collection of puzzles and exercises in key areas of text algorithms and combinatorics on words offers graduate students and researchers a pleasant and direct way to learn and practice with advanced concepts. The problems are drawn from a large range of scientific publications, both classic and new. Building up from the basics, the book goes on to showcase problems in combinatorics on words (including Fibonacci or Thue-Morse words), pattern matching (including Knuth-Morris-Pratt and Boyer-Moore like algorithms), efficient text data structures (including suffix trees and suffix arrays), regularities in words (including periods and runs) and text compression (including Huffman, Lempel-Ziv and Burrows-Wheeler based methods).
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Models and Algorithms for Biomolecules and Molecular Networks
By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithmsSampling techniques for estimating evolutionary rates and generating molecular structuresAccurate computation of probability landscape of stochastic networks, solving discrete chemical master equationsEnd-of-chapter exercises
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Discrete Problems in Nature Inspired Algorithms
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 the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.
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Machine Learning Algorithms in Depth
Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price SimulationImage Denoising using Mean-Field Variational InferenceEM algorithm for Hidden Markov ModelsImbalanced Learning, Active Learning and Ensemble LearningBayesian Optimisation for Hyperparameter TuningDirichlet Process K-Means for Clustering ApplicationsStock Clusters based on Inverse Covariance EstimationEnergy Minimisation using Simulated AnnealingImage Search based on ResNet Convolutional Neural NetworkAnomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.
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Algorithms for VLSI Physical Design Automation
Algorithms for VLSI Physical Design Automation is a core reference text for graduate students and CAD professionals. It provides a comprehensive treatment of the principles and algorithms of VLSI physical design. Algorithms for VLSI Physical Design Automation presents the concepts and algorithms in an intuitive manner. Each chapter contains 3-4 algorithms that are discussed in detail. Additional algorithms are presented in a somewhat shorter format. References to advanced algorithms are presented at the end of each chapter. Algorithms for VLSI Physical Design Automation covers all aspects of physical design. The first three chapters provide the background material while the subsequent chapters focus on each phase of the physical design cycle. In addition, newer topics like physical design automation of FPGAs and MCMs have been included. The author provides an extensive bibliography which is useful for finding advanced material on a topic. Algorithms for VLSI Physical Design Automation is an invaluable reference for professionals in layout, design automation and physical design.
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Foundations of Software Science and Computation Structures
This book constitutes the proceedings of the 20th International Conference on Foundations of Software Science and Computation Structures, FOSSACS 2017, which took place in Uppsala, Sweden in April 2017, held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017. The 32 papers presented in this volume were carefully reviewed and selected from 101 submissions. They were organized in topical sections named: coherence spaces and higher-order computation; algebra and coalgebra; games and automata; automata, logic and formal languages; proof theory; probability; concurrency; lambda calculus and constructive proof; and semantics and category theory.
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Fun with Algorithms
This book constitutes the refereed proceedings of the 7th International Conference, FUN 2014, held in July 2014 in Lipari Island, Sicily, Italy.The 29 revised full papers were carefully reviewed and selected from 49 submissions. They feature a large variety of topics in the field of the use, design and analysis of algorithms and data structures, focusing on results that provide amusing, witty but nonetheless original and scientifically profound contributions to the area. In particular, algorithmic questions rooted in biology, cryptography, game theory, graphs, the internet, robotics and mobility, combinatorics, geometry, stringology, as well as space-conscious, randomized, parallel, distributed algorithms and their visualization are addressed.
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Object-Oriented Approach to Problem Solving and Machine Learning with Python
This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.
R 2,982.49

Discrete Structures
The aim of this text is to introduce discrete mathematics to beginning students of mathematics or computer science. It does this by bringing some coherency into the seemingly incongruent subjects that compose discrete math, such as logic, set theory, algebra, and combinatorics. It emphasizes their theoretical foundations and illustrates proofs along the way. The book prepares readers for the analysis of algorithms by discussing asymptotic analysis and a discrete calculus for sums. The book also deduces combinatorial methods from the foundations that are laid out. Unlike other texts on this subject, there is a greater emphasis on foundational material that leads to a better understanding. To further assist the reader in grasping and practicing concepts, roughly 690 exercises are provided at various levels of difficulty. Readers are encouraged to study the examples in the text and solve as many of the exercises as possible.The text is intended for freshman or sophomore undergraduate students in mathematics, computer science, or similar majors. The assumed background is precalculus. The chapter dependency chart included is designed to help students, independent readers, and instructors follow a systematic path for learning and teaching the material, with the option to explore material in later chapters.
R 2,564.00

Applied AI for Enterprise Java Development
As a Java enterprise developer or architect, you know that embracing AI isn't just optional-it's critical to keeping your competitive edge. The question is, how can you skillfully incorporate these groundbreaking AI technologies into your applications without getting mired in complexity?Enter this clear-cut, no-nonsense guide to integrating generative AI into your Java enterprise ecosystem. With insights from authors Alex Soto Bueno, Markus Eisele, and Natale Vinto, you'll learn to marry the robustness of Java's enterprise world with the dynamism of AI. It's more than just a how-to-it's a way to elevate enterprise software with savvy AI integrations, ensuring your skills and your applications remain on the cutting edge.Inside, you'll unlock the power to:Demystify GenAI's role and impact on contemporary software developmentCraft actionable, AI-driven applications using Java's rich ecosystem of open source frameworksImplement field-tested AI patterns tailored for prod-ready, enterprise-strength applicationsAccess and integrate top-tier open source AI models with Java's Inference APIsNavigate the Java framework landscape with AI-centric agility and confidence
R 1,505.00

Algorithms for Convex Optimization
In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.
R 4,342.15

Beginner's Guide to Code Algorithms
Do you have creative ideas that you wish you could transform into code?Do you want to boost your problem solving and logic skills?Do you want to enhance your career by adopting an algorithmic mindset?In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner’s Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code – building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentationThis book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.
R 2,980.62

Distributed Algorithms
This book constitutes the refereed proceedings of the 11th International Workshop on Distributed Algorithms, WDAG '97, held in Saarbrücken, Germany, in September 1997.The volume presents 20 revised full papers selected from 59 submissions. Also included are three invited papers by leading researchers. The papers address a variety of current issues in the area of distributed algorithms and, more generally, distributed systems such as various particular algorithms, randomized computing, routing, networking, load balancing, scheduling, message-passing, shared-memory systems, communication, graph algorithms, etc.
R 1,564.46
















































