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Algorithmic Aspects in Information and Management
This volume constitutes the proceedings of the 11th International Conference on Algorithmic Aspects in Information and Management, AAIM 2016, held in Bergamo, Italy, in July 2016.The 18 revised full papers presented were carefully reviewed and selected from 41 submissions. The papers deal with current trends of research on algorithms, data structures, operation research, combinatorial optimization and their applications.
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Algorithms and Computation
This book constitutes the refereed proceedings of the 26th InternationalSymposium on Algorithms and Computation, ISAAC 2015, held in Nagoya, Japan, inDecember 2015.The 65 revised full papers presented together with 3 invited talks were carefullyreviewed and selected from 180 submissions for inclusion in the book. The focusof the volume is on the following topics: computational geometry; datastructures; combinatorial optimization and approximation algorithms; randomizedalgorithms; graph algorithms and FPT; computational complexity; graph drawingand planar graphs; online and streaming algorithms; and string and DNAalgorithms.
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Algorithms in Bioinformatics
We are pleased to present the proceedings of the 5th Workshop on Algorithms in Bioinformatics (WABI 2005) which took place in Mallorca, Spain, October 3-6, 2005. The WABI 2005 workshop was part of the ?ve ALGO 2005 conf- ence meetings, which, in addition to WABI, included ESA, WAOA, IWPEC, and ATMOS. WABI 2005 was sponsored by EATCS (the European Assoc- tion for Theoretical Computer Science), the ISCB (the International Society for Computational Biology), the Universitat Polit' ecnica de Catalunya, the U- versitat de les Illes Balears, and the Ministerio de Educaci' on y Ciencia. See http://www.lsi.upc.edu/"wabi05/ for more details. The Workshop on Algorithms in Bioinformatics highlights research work speci?cally developed to address algorithmic problems in biosequence analysis. Theemphasisisthereforeonstatisticalandprobabilisticalgorithmsthataddress important problems in the ?eld of molecular and structural biology. At present, given the enormous scienti?c and technical e?orts in functional and structural genomics, the relevance of the problem is therefore constrained by the need for sound, e?cient and specialized algorithms, capable of achieving solutions that can be tested by the biological community.Indeed the ultimate goal is to - plement algorithms capable of extracting real features from real biological data sets. Therefore the workshop aims to present recent research results, including signi?cant work in progress, and to identify and explore directions of future research.
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Python Algorithms
Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.
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Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety
This book constitutes the refereed proceedings of the 14th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2018, held in Poznań, Poland, in September 2018, during the IFIP World Computer Congress.It consists of 38 carefully reviewed papers selected from 102 submissions. The papers are organized in topical sections, namely big data and cloud computing; architectures, structures and algorithms for efficient data processing; artificial intelligence, data mining and knowledge discovery; text mining, natural language processing, ontologies and semantic web; image analysis and multimedia mining.
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Parallel Algorithms for Irregularly Structured Problems
This book presents the proceedings of the Second International Workshop on Parallel Algorithms for Irregularly Structured Problems, IRREGULAR '95, held in Lyon, France in September 1995. This workshop series addresses issues related to deriving efficient parallel solutions to irregularly structured problems and aims at fostering cooperation between practitioners and theoreticians in the field.Besides three invited papers, 20 full papers and eight short contributions are presented, all selected during a highly competitive refereeing process; the volume is organized in sections on programming methods and compiling techniques, mapping and scheduling, applications, and optimization.
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Algorithms
This is the proceedings of the SIGAL International Symposium on Algorithms held at CSK Information Education Center, Tokyo, Japan, August 16-18, 1990. SIGAL (Special Interest Group on Algorithms) was organized within the Information Processing Society of Japan in 1988 to encourage research in the field of discrete algorithms, and held 6-8 research meetings each year. This symposium is the first international symposium organized by SIGAL. In response to the call for papers, 88 papers were submitted from around the world. The program committee selected 34 for presentation at the symposium. The symposium also included 5 invited lectures and 10 invited presentations. The subjects of the papers range widely in the field of discrete algorithms in theoretical computer science. Keywords for these subjects are: computational geometry, graph algorithms, complexity theory, parallel algorithms, distributed computing, and computational algebra.
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Functional Data Structures in R
Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You’ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You’ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R.By the end of Functional Data Structures in R, you’ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications.What You'll LearnCarry out algorithmic programming in R Use abstract data structures Work with both immutable and persistent data Emulate pointers and implement traditional data structures in RBuild new versions of traditional data structures that are knownWho This Book Is ForExperienced or advanced programmers with at least a comfort level with R. Some experience with data structures recommended.
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Java Data Mining: Strategy, Standard, and Practice
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard.
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Live Data Structures in Logic Programs
A common hazard for implementations of applicativeprogramming languages is the excessive creation of garbagecells during program execution. The available run-timegarbage collecting processes are expensive in time and oftenrequire a periodic disruption of the program execution. Thepresent book addresses the problem of memory re-use forlogic programs through program analysis rather than byrun-time garbage collection. The static analysis isconstructed as an application of abstractinterpretation forlogic programs. The starting point is a previously developedapplication of integrated type and mode analysis, whichbasically supplies a description of the logical terms towhich program variables can be bound at run time. Thecontribution of the book consists of a modular extension ofthe abstract domain and operations in order to deriverun-time properties concerning the sharing and liveness ofterm substructures dynamically created during programexecution. Alsoillustrated is how such information can beused by the compiler to improve the allocation of run-timestructures and to automatically introduce destructiveassignments in logic languages in a safe and transparentway, thereby shifting some part of the run-time storagereclamation overhead to compile time.
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First Course in Algorithms Through Puzzles
This textbook introduces basic algorithms and explains their analytical methods. All algorithms and methods introduced in this book are well known and frequently used in real programs. Intended to be self-contained, the contents start with the basic models, and no prerequisite knowledge is required. This book is appropriate for undergraduate students in computer science, mathematics, and engineering as a textbook, and is also appropriate for self-study by beginners who are interested in the fascinating field of algorithms. More than 40 exercises are distributed throughout the text, and their difficulty levels are indicated. Solutions and comments for all the exercises are provided in the last chapter. These detailed solutions will enable readers to follow the author's steps to solve problems and to gain a better understanding of the contents.
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WALCOM: Algorithms and Computation
This book constitutes the proceedings of the 12th International Workshop on Algorithms and Computation, WALCOM 2018, held in Dhaka, Bangladesh, in March 2018.The 22 full papers presented were carefully reviewed and selected from 50 submissions. The papers cover diverse areas of algorithms and computation, such as approximation algorithms, computational geometry, combinatorial algorithms, computational biology, computational complexity, data structures, graph and network algorithms, and online algorithms.
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Algorithms and Architectures for Parallel Processing
The two-volume set LNCS 11944-11945 constitutes the proceedings of the 19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019, held in Melbourne, Australia, in December 2019. The 73 full and 29 short papers presented were carefully reviewed and selected from 251 submissions. The papers are organized in topical sections on: Parallel and Distributed Architectures, Software Systems and Programming Models, Distributed and Parallel and Network-based Computing, Big Data and its Applications, Distributed and Parallel Algorithms, Applications of Distributed and Parallel Computing, Service Dependability and Security, IoT and CPS Computing, Performance Modelling and Evaluation.
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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery
This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016.It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems.
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Graphs, Networks and Algorithms
From the reviews of the previous editions ".... The book is a first class textbook and seems to be indispensable for everybody who has to teach combinatorial optimization. It is very helpful for students, teachers, and researchers in this area. The author finds a striking synthesis of nice and interesting mathematical results and practical applications. ... the author pays much attention to the inclusion of well-chosen exercises. The reader does not remain helpless; solutions or at least hints are given in the appendix. Except for some small basic mathematical and algorithmic knowledge the book is self-contained. ..." K.Engel, Mathematical Reviews 2002 The substantial development effort of this text, involving multiple editions and trailing in the context of various workshops, university courses and seminar series, clearly shows through in this new edition with its clear writing, good organisation, comprehensive coverage of essential theory, and well-chosen applications. The proofs of important results and the representation of key algorithms in a Pascal-like notation allow this book to be used in a high-level undergraduate or low-level graduate course on graph theory, combinatorial optimization or computer science algorithms. The well-worked solutions to exercises are a real bonus for self study by students. The book is highly recommended. P .B. Gibbons, Zentralblatt für Mathematik 2005 Once again, the new edition has been thoroughly revised. In particular, some further material has been added: more on NP-completeness (especially on dominating sets), a section on the Gallai-Edmonds structure theory for matchings, and about a dozen additional exercises – as always, with solutions. Moreover, the section on the 1-factor theorem has been completely rewritten: it now presents a short direct proof for the more general Berge-Tutte formula. Several recent research developments are discussed and quite a few references have been added.
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Programming GPS and OpenStreetMap Applications with Java
Written by an expert in the development of GPS systems with digital maps and navigation, Programming GPS and OpenStreetMap Applications with Java: The RealObject Application Framework provides a concrete paradigm for object-oriented modeling and programming. It presents a thorough introduction to the use of available global positioning data for the development of applications involving digital maps. The author first describes the different formats of GPS data and digital maps and shows how to use recorded GPS traces to replay and display this data on a digital map. Then, he works through in detail the processing steps of obtaining dedicated data from OpenStreetMaps and how to extract a network for a simple navigation application. For each topic covered—GPS data, OpenStreetMaps, and navigation—Java code is developed that can easily be adapted to the readers’ needs and locality.Finally, all components are put together in a sample computer-game application modeled on the well-known board game, Scotland Yard. The computer game is intended to be a basis from which readers can develop and customize their own application for their desired geographical area. The developed application can be "published" on the Internet and made available for interactive multiplayer competition.This book provides a fun and interesting way to learn distributed programming with Java and real-world data. Open-source software is available on a companion website at www.roaf.de
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Parallel Architecture, Algorithm and Programming
This book constitutes the refereed proceedings of the 8th International Symposium on Parallel Architecture, Algorithm and Programming, PAAP 2017, held in Haikou, China, in June 2017. The 50 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 192 submissions. The papers deal with research results and development activities in all aspects of parallel architectures, algorithms and programming techniques.
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Fundamental Algorithms for Permutation Groups
This is the first-ever book on computational group theory.It provides extensive and up-to-date coverage of thefundamental algorithms for permutation groups with referenceto aspects of combinatorial group theory, soluble groups,and p-groups where appropriate.The book begins with a constructive introduction to grouptheory and algorithms for computing with small groups,followed by a gradual discussion of the basic ideas of Simsfor computing with very large permutation groups, andconcludes with algorithms that use group homomorphisms, asin the computation of Sylowsubgroups. No background ingroup theory is assumed.The emphasis is on the details of the data structures andimplementation which makes the algorithms effective whenapplied to realistic problems. The algorithms are developedhand-in-hand with the theoretical and practicaljustification.All algorithms are clearly described,examples are given, exercises reinforce understanding, anddetailed bibliographical remarks explain the history andcontext of the work.Much of the later material on homomorphisms, Sylowsubgroups, and soluble permutation groups is new.
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Management and Processing of Complex Data Structures
This volume presents the proceedings of the third workshop on Information Systems and Artificial Intelligence, organized by the German Computer Science Society. The 11 invited contributions by well known researchers and developers working in the fields of databases and knowledge representation systems are centered around the topic of management and processing of complex data structures; they give a representative snapshot of the state-of-the-art in this fruitful interdisciplinary research area important for further progress in both, information systems and artificial intelligence. Most of the papers stress the demands for new or extended formalisms and their deductive capabilities, including an analysis of their formal properties for managing complex structures.
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Introduction to Python Programming and Data Structures, Global Edition
For introductory courses in Python Programming and Data Structures. A fundamentals first approach to programming helps students create efficient, elegant code. Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.
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Algorithms and Architectures for Parallel Processing
The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows:Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.
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Algorithms and Theory of Computation Handbook, Volume 1
Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory. This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.
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Core Java, Volume II
The Classic Guide to the Java Programming Language--Fully Updated through Java 25 Core Java is the leading no-nonsense tutorial and reference for experienced programmers who want to write robust Java code for real-world applications. Now, Core Java, Volume II: Advanced Features, Fourteenth Edition, has been revised to cover the new features and enhancements in the Java 25 long-term support release. As always, all chapters have been completely updated, outdated material has been removed, and the new APIs are covered in detail. This volume focuses on the advanced topics that a programmer needs to know for professional software development and includes authoritative coverage of fi le processing, networking, databases, security, internationalization, compiling and scripting, and foreign functions, as well as complete chapters on the Streams, XML, and Date and Time APIs. In addition, the chapters on Swing and Graphics cover techniques that are applicable to both client-side user interfaces and server-side generation of graphics and images. Cay S. Horstmann clearly explains sophisticated new features with depth and completeness and demonstrates how to use them to build professional-quality applications. Horstmann's thoroughly tested sample code reflects modern Java style and best practices. The examples are carefully crafted for easy understanding and maximum practical value, so you can rely on them to jump-start your own programs. Effectively use Java streams, including new Java 25 features such as stream gatherersMaster advanced techniques, idioms, and best practices for writing reliable Java codeMake the most of enhanced Java I/O APIs, object serialization, and regular expressionsConnect to network services, harvest web data with the HTTP/2 client, and serve data with the built-in web server or implement your own serverProcess code via the Scripting and Compiler APIs, and generate code with the new Class File APILeverage the Java security model, user authentication, and the security library's cryptographic functionsLearn powerful new APIs for accessing foreign functions and memory "This is the definitive reference and instructional work for Java and the Java ecosystem."--Andrew Binstock, Java Magazine See Core Java, Volume I: Fundamentals, Fourteenth Edition, for expert coverage of Java programming fundamentals, including objects, generics, collections, lambda expressions, concurrency, modularity, and functional programming. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
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Lecture Notes on Bucket Algorithms
Hashing algorithms scramble data and create pseudo-uniform data distribu- tions. Bucket algorithms operate on raw untransformed data which are parti- tioned Into groups according to membership In equl-slzed d-dlmenslonal hyperrec- tangles, called cells or buckets. The bucket data structure Is rather sensitive to the distribution of the data. In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the dis- tribution of the data. The results are Illustrated on standard searching, sorting and selection problems, as well as on a variety of problems In computational geometry and operations research. The notes grew partially from a graduate course on probability theory In computer science. I wish to thank Elizabeth Van Gulick for her help with the manuscript, and David Avis, Hanna AYukawa, Vasek Chvatal, Beatrice Devroye, Hossam EI Glndy, Duncan McCallum, Magda McCallum, Godfrled Toussaint and Sue Whltesldes"for making the School of Computer Science at McGill University such an enjoyable place. The work was supported by NSERC Grant A3456 and by FCAC Grant EQ-1679.INTRODUCTION 1 INTRODUCTION It Is not a secret that methods based upon the truncation of data have good expected time performance. For example, for nice distributions of the data, searching Is often better done via a hashing data structure Instead of via a search tree. The speed one observes In practice Is due to the fact that the truncation operation Is a constant time operation.
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Algorithms and Architectures for Parallel Processing
This two volume set LNCS 8285 and 8286 constitutes the proceedings of the 13th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2013, held in Vietri sul Mare, Italy in December 2013. The first volume contains 10 distinguished and 31 regular papers selected from 90 submissions and covering topics such as big data, multi-core programming and software tools, distributed scheduling and load balancing, high-performance scientific computing, parallel algorithms, parallel architectures, scalable and distributed databases, dependability in distributed and parallel systems, wireless and mobile computing. The second volume consists of four sections including 35 papers from one symposium and three workshops held in conjunction with ICA3PP 2013 main conference. These are 13 papers from the 2013 International Symposium on Advances of Distributed and Parallel Computing (ADPC 2013), 5 papers of the International Workshop on Big Data Computing (BDC 2013), 10 papers of the International Workshop on Trusted Information in Big Data (TIBiDa 2013) as well as 7 papers belonging to Workshop on Cloud-assisted Smart Cyber-Physical Systems (C-Smart CPS 2013).
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Algorithms for Graphics and Image Processing
The technological developments of the last ten years have made com puter graphics and image processing by computer popular. Pictorial pat tern recognition has also shown significant progress. Clearly, there exist overlapping interests among the three areas of research. Graphic displays are of concern to anyone involved in image processing or pic torial pattern recognition and many problems in graphics require methodologies from image processing for their solutions. The data structures used in all three areas are similar. It seems that there is a common body of knowledge underlying all three areas, pictorial informa tion processing by computer. The novelty of these fields makes it difficult to design a course or to a write a book covering their basic concepts. Some of the treatises on graphics focus on the hardware and methods of current interest while treatises on image processing often emphasize applications and classical signal processing. The fast evolution of technology causes such material to lose its relevance. For example, the development of optical fibers has reduced the importance of bandwidth compression.
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50 Algorithms Every Programmer Should Know - Second Edition
Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition overhaulPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesFamiliarize yourself with advanced deep learning architecturesExplore newer topics, such as handling hidden bias in data and algorithm explainabilityGet to grips with different programming algorithms and choose the right data structures for their optimal implementationBook DescriptionThe ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.What you will learnDesign algorithms for solving complex problemsBecome familiar with neural networks and deep learning techniquesExplore existing data structures and algorithms found in Python librariesImplement graph algorithms for fraud detection using network analysisDelve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examplesCreate a recommendation engine that suggests relevant movies to subscribersGrasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMsWho this book is forThis computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code.Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful.Python programming experience is a must, knowledge of data science will be helpful but not n
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Composite Data Structures and Modularization
This book covers C-Programming focussing on its practical side. Volume 2 deals mainly with composite data structures and their composition. An extensive use of figures and examples help to give a clear description of concepts and help the reader to gain a systematic understanding of the programming language.
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Algorithms and Architectures for Parallel Processing
The four-volume set LNCS 11334-11337 constitutes the proceedings of the 18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018, held in Guangzhou, China, in November 2018.The 141 full and 50 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Distributed and Parallel Computing; High Performance Computing; Big Data and Information Processing; Internet of Things and Cloud Computing; and Security and Privacy in Computing.
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Algorithms and Architectures for Parallel Processing
The four-volume set LNCS 11334-11337 constitutes the proceedings of the 18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018, held in Guangzhou, China, in November 2018.The 141 full and 50 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Distributed and Parallel Computing; High Performance Computing; Big Data and Information Processing; Internet of Things and Cloud Computing; and Security and Privacy in Computing.
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Automatic Coding: Choice of Data Structures
1.0 2 information structures, and the runtime efficiency available using lower level data structures. We believe these runtime inefficiencies can be remedied by providing a library of representations for the information structures and a user assisted automatic system to choose appropriate elements from this library for the user's programs. The main problems in such an automatic approach are: 1). Building a library of representations; 2). Characterizing the properties of these representations; 3). understanding how the user's program actually uses the abstract information structures; and -4). efficiently matching the user program needs with the properties of the known representations. The research reported here is an attempt to demonstrate the feasibility of such automatic representation selection. We allow the user to express data in terms of relations, sets, and sequences. Our system then obtains information by analysis of the program, execution statement profiles and interrogation of the user. Using that information, the system selects efficient (in terms of time and space) low level implementations for the user's information structures from a fixed library of information structure representations. Though we have considered only a few abstract information structures (those available in our programming language, SAIL) we believe the techniques used in this system are generally applicable.
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Algorithms and Programming
This text is structured in a problem-solution format that requires the student to think through the programming process. New to the second edition are additional chapters on suffix trees, games and strategies, and Huffman coding as well as an Appendix illustrating the ease of conversion from Pascal to C.
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Bioinformatics Algorithms
Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers: General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.
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Algorithms and Discrete Applied Mathematics
This book constitutes the proceedings of the Third International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2017, held in Goa, India, in February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 103 submissions. They deal with the following areas: algorithms, graph theory, codes, polyhedral combinatorics, computational geometry, and discrete geometry.
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Introduction To The Analysis Of Algorithms, An (3rd Edition)
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 succinct, this edition is mathematically rigorous, covering the foundations for both computer scientists and mathematicians with interest in the algorithmic foundations of Computer Science.Besides expositions on traditional algorithms such as Greedy, Dynamic Programming and Divide & Conquer, the book explores two classes of algorithms that are often overlooked in introductory textbooks: Randomised and Online algorithms — with emphasis placed on the algorithm itself. The book also covers algorithms in Linear Algebra, and the foundations of Computation.The coverage of Randomized and Online algorithms is timely: the former have become ubiquitous due to the emergence of cryptography, while the latter are essential in numerous fields as diverse as operating systems and stock market predictions.While being relatively short to ensure the essentiality of content, a strong focus has been placed on self-containment, introducing the idea of pre/post-conditions and loop invariants to readers of all backgrounds, as well as all the necessary mathematical foundations. The programming exercises in Python will be available on the web (see www.msoltys.com/book for the companion web site).
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Algorithms on Strings, Trees, and Sequences
String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals.
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Compressed Data Structures for Strings
Data compression is mandatory to manage massive datasets, indexing is fundamental to query them. However, their goals appear as counterposed: the former aims at minimizing data redundancies, whereas the latter augments the dataset with auxiliary information to speed up the query resolution. In this monograph we introduce solutions that overcome this dichotomy. We start by presenting the use of optimization techniques to improve the compression of classical data compression algorithms, then we move to the design of compressed data structures providing fast random access or efficient pattern matching queries on the compressed dataset. These theoretical studies are supported by experimental evidences of their impact in practical scenarios.
R 1,528.57
Java Persistence with Spring Data and Hibernate
Master Java persistence using the industry-leading tools Spring Data and Hibernate. In Java Persistence with Spring Data and Hibernate you will learn: Mapping persistent classes, value types, and inheritanceMapping collections and entity associationsProcessing transactions with Spring Data and HibernateCreating fetch plans, strategies, and profilesFiltering dataBuilding Spring Data REST projectsUsing Java persistence with non-relational databasesQuerying JPA with QueryDSLTesting Java persistence applications Java Persistence with Spring Data and Hibernate teaches you the ins-and-outs of Java persistence with hands-on examples using Spring Data, JPA and Hibernate. The book carefully analyzes the capabilities of the major Java persistence tools, and guides you through the most common use cases. You’ll learn how to make and utilize mapping strategies, and efficiently test Java persistence applications. The practical techniques are demonstrated with both relational and non-relational databases. about the technology Persistence enables an application’s data to exist for the long term, even after a program is stopped or terminated. Whether you’re saving state from session to session or maintaining long-term records, Java persistence tools like Spring Data, JPA, and Hibernate help deliver the object relational mapping that connects code’s objects with your database. about the book Java Persistence with Spring Data and Hibernate explores persistence with the most popular available tools. You’ll benefit from detailed coverage of Spring Data JPA, Spring Data JDBC, Spring Data REST, JPA, and Hibernate, comparing and contrasting the alternatives so you can pick what’s best for your code. Begin with a hands-on introduction to object-relational mapping (ORM), then dive into mapping strategies for linking up objects and your database. You’ll learn about the different approach to transactions for both Hibernate and Spring Data, and even how to deliver Java persistence with non-relational databases. Finally, you’ll explore testing strategies for persistent applications to keep your code clean and bug free.
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The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
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The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
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