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Algorithms and Complexity
The papers in this volume were presented at the Fourth Italian Conference on Algorithms and Complexity (CIAC 2000). The conference took place on March 1-3, 2000, in Rome (Italy), at the conference center of the University of Rome \La Sapienza". This conference was born in 1990 as a national meeting to be held every three years for Italian researchers in algorithms, data structures, complexity, and parallel and distributed computing. Due to a signi cant participation of foreign reaserchers, starting from the second conference, CIAC evolved into an international conference. In response to the call for papers for CIAC 2000, there were 41 subm- sions, from which the program committee selected 21 papers for presentation at the conference. Each paper was evaluated by at least three program committee members. In addition to the selected papers, the organizing committee invited Giorgio Ausiello, Narsingh Deo, Walter Ruzzo, and Shmuel Zaks to give plenary lectures at the conference. We wish to express our appreciation to all the authors of the submitted papers, to the program committee members and the referees, to the organizing committee, and to the plenary lecturers who accepted our invitation.
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Design and Analysis of Algorithms
The text covers important algorithm design techniques, such as greedy algorithms, dynamic programming, and divide-and-conquer, and gives applications to contemporary problems. Techniques including Fast Fourier transform, KMP algorithm for string matching, CYK algorithm for context free parsing and gradient descent for convex function minimization are discussed in detail. The book's emphasis is on computational models and their effect on algorithm design. It gives insights into algorithm design techniques in parallel, streaming and memory hierarchy computational models. The book also emphasizes the role of randomization in algorithm design, and gives numerous applications ranging from data-structures such as skip-lists to dimensionality reduction methods.
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Combinatorial Algorithms
This book constitutes the thoroughly referred post-workshop proceedings of the 23rd International Workshop on Combinatorial Algorithms, IWOCA 2012, held in Krishnankoil, Tamil Nadu, India, in July 2012.The 32 revised full papers presented were carefully reviewed and selected from a total of 88 submissions. The papers are organized in topical sections in algorithms and data Structures, applications (including Bioinformatics, Networking, etc.), combinatorics of words and strings, combinatorial optimization, combinatorial enumeration, decompositions and combinatorial designs, complexity theory (structural and computational), computational biology and graph theory and combinatorics submissions.
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Algorithms - ESA 2001
This book constitutes the refereed proceedings of the 9th Annual European Symposium on Algorithms, ESA 2001, held in Aarhus, Denmark, in August 2001.The 41 revised full papers presented together with three invited contributions were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on caching and prefetching, online algorithms, data structures, optimization and approximation, sequences, scheduling, shortest paths, geometry, distributed algorithms, graph algorithms, pricing, broadcasting and multicasting, graph labeling and graph drawing, and graphs.
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Data Structures for Engineers and Scientists Using Python
The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using queue model, and topological sorting.This book:Discusses the implementation of various data structures such as an array, stack, queue, tree, and graph along with sorting and searching algorithms. Includes programming tips to highlight important concepts and help readers avoid common programming errors. Presents each concept of data structure with a different approach and implements the same using Python programming. Offers rich chapter-end pedagogy including objective-type questions (with answers), review questions, and programming exercises to facilitate revision. Covers fundamentals of Python up to object-oriented concepts including regular expression. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
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Algorithms in Bioinformatics
These proceedings contain papers from the 2009 Workshop on Algorithms in Bioinformatics (WABI), held at the University of Pennsylvania in Philadelphia, Pennsylvania during September 12–13, 2009. WABI 2009 was the ninth annual conference in this series, which focuses on novel algorithms that address imp- tantproblemsingenomics,molecularbiology,andevolution.Theconference- phasizes research that describes computationally e?cient algorithms and data structures that have been implemented and tested in simulations and on real data. WABI is sponsored by the European Association for Theoretical C- puter Science (EATCS) and the International Society for Computational Bi- ogy (ISCB). WABI 2009 was supported by the Penn Genome Frontiers Institute and the Penn Center for Bioinformatics at the University of Pennsylvania. For the 2009 conference, 90 full papers were submitted for review by the Program Committee, and from this strong ?eld of submissions, 34 papers were chosen for presentation at the conference and publication in the proceedings. The ?nal programcovered a wide range of topics including gene interaction n- works, molecular phylogeny, RNA and protein structure, and genome evolution.
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Programming Algorithms in Lisp
Master algorithms programming using Lisp, including the most important data structures and algorithms. This book also covers the essential tools that help in the development of algorithmic code to give you all you need to enhance your code.Programming Algorithms in Lisp shows real-world engineering considerations and constraints that influence the programs that use these algorithms. It includes practical use cases of the applications of the algorithms to a variety of real-world problems. What You Will LearnProgram algorithms using the Lisp programming languageWork with data structures, arrays, key-values, hash-tables, trees, graphs, and moreUse dynamic programming Program using stringsWork with approximations and compression Who This Book Is For Intermediate Lisp programmers wanting to do algorithms programming. A very experienced non-Lisp programmer may be able to benefit from this book as well.
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Algorithms and Computation
This book constitutes the refereed proceedings of the 23rd International Symposium on Algorithms and Computation, ISAAC 2012, held in Taipei, Taiwan, in December 2012. The 68 revised full papers presented together with three invited talks were carefully reviewed and selected from 174 submissions for inclusion in the book. This volume contains topics such as graph algorithms; online and streaming algorithms; combinatorial optimization; computational complexity; computational geometry; string algorithms; approximation algorithms; graph drawing; data structures; randomized algorithms; and algorithmic game theory.
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Algorithms: A Top-down Approach
This comprehensive compendium provides a rigorous framework to tackle the daunting challenges of designing correct and efficient algorithms. It gives a uniform approach to the design, analysis, optimization, and verification of algorithms. The volume also provides essential tools to understand algorithms and their associated data structures.This useful reference text describes a way of thinking that eases the task of proving algorithm correctness. Working through a proof of correctness reveals an algorithm's subtleties in a way that a typical description does not. Algorithm analysis is presented using careful definitions that make the analyses mathematically rigorous.Related Link(s)
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WALCOM: Algorithms and Computation
This book constitutes the proceedings of the 13th International Conference and Workshop on Algorithms and Computation, WALCOM 2019, held in Guwahati, India, in February/ March 2019.The 30 full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical headings on the facility location problem; computational geometry; graph drawing; graph algorithms; approximation algorithms; miscellaneous; data structures; parallel and distributed algorithms; and packing and covering.
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Data Structures and Program Design Using C
Data structures provide a means to manage large amounts of information such as large databases, using SEO, and creating Internet/Web indexing services. The book is designed to present fundamentals of data structures for beginners using the C programming language. Practical analogies using real world applications are integrated throughout the text to explain the technical concepts presented. Features:Covers data structure fundamentals using CNumerous tips and practical applications enhance understanding of concepts
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Algorithms and Architectures for Parallel Processing
This fourvolume set LNCS 9528, 9529, 9530 and 9531 constitutes the refereed proceedingsof the 15th International Conference on Algorithms and Architectures for ParallelProcessing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015.The 219revised full papers presented together with 77 workshop papers in these fourvolumes were carefully reviewed and selected from 807 submissions (602 fullpapers and 205 workshop papers). The first volume comprises the followingtopics: parallel and distributed architectures; distributed and network-basedcomputing and internet of things and cyber-physical-social computing. Thesecond volume comprises topics such as big data and its applications andparallel and distributed algorithms. The topics of the third volume are:applications of parallel and distributed computing and service dependabilityand security in distributed and parallel systems. The covered topics of the fourthvolume are: software systems and programming models and performance modelingand evaluation.
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Experimental Algorithms
This book constitutes the refereed proceedings of the 14th International Symposium on Experimental Algorithms, SEA 2015, held in Paris, France, in June/July 2015.The 30 revised full papers presented were carefully reviewed and selected from 76 submissions. The main theme of the symposium is the role of experimentation and of algorithm engineering techniques in the design and evaluation of algorithms and data structures. The papers are grouped in topical sections on data structures, graph problems, combinatorial optimization, scheduling and allocation, and transportation networks.
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Algorithms and Computation
This volume gives the proceedings of ISAAC '92, the ThirdInternational Symposium on Algorithms and Computation, heldin Nagoya, Japan, December 1992.The first symposium was held in Tokyo in 1990, as the firstinternational symposium organized by SIGAL (Special InterestGroupon Algorithms in the Information Processing Society ofJapan) to serve as anannual international forum in Asia forresearchers in the area of algorithms. The second symposiumwas held in Taipei, Taiwan in 1991, where it was decidedthat computation would be included in the main scope of thesymposium and that ISAAC would be its name.ISAAC '92 focuses on topics in design and analysis ofalgorithms, computational complexity, and theory ofcomputation, including algorithms and data structures,parallel/distributed computing, automata and formallanguages, probabilistic/approximation algorithms,computability and complexity, term rewriting systems, andcomputational geometry. The volume contains the acceptedcontributed papers and the invited papers.
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50 Algorithms Every Programmer Should Know
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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Introduction To The Analysis Of Algorithms (Fourth Edition)
An Introduction to the Analysis of Algorithms is a comprehensive textbook that presents the fundamental methods for designing and analyzing computational algorithms through rigorous mathematical frameworks and practical implementation guidance. The book systematically explores major algorithmic paradigms including greedy algorithms, divide and conquer, dynamic programming, online algorithms, randomized algorithms, and parallel algorithms in linear algebra, providing detailed analysis of correctness and performance for each approach.The text emphasizes algorithm design techniques and formal analysis using pre/post-conditions and loop invariants, while covering essential computational foundations including automata theory, regular expressions, and complexity analysis. A new chapter on machine learning introduces students to this rapidly growing field, covering both supervised learning methods like regression and classification, and unsupervised techniques such as clustering, providing a bridge between traditional algorithmic thinking and modern data-driven approaches. The book also addresses practical considerations such as algorithm implementation, optimization techniques, and real-world applications across various domains.Intended for undergraduate and graduate students in computer science and mathematics, the self-contained presentation includes all necessary background material, worked examples, and extensive problem sets, making it suitable as both a classroom textbook and a comprehensive reference for anyone seeking to master algorithmic problem-solving and analysis.
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Mining of Data with Complex Structures
Mining of Data with Complex Structures:- Clarifies the type and nature of data with complex structure including sequences, trees and graphs- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.- Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.- Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.- Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.- Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.- Details the extension of the TMG framework for sequence mining- Provides an overview of the future research direction with respect to technical extensions and application areasThe primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.
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Learning Algorithms
When it comes to writing efficient code, every software professional needs to have an effective working knowledge of algorithms. In this practical book, author George Heineman (Algorithms in a Nutshell) provides concise and informative descriptions of key algorithms that improve coding. Software developers, testers, and maintainers will discover how algorithms solve computational problems creatively.Each chapter builds on earlier chapters through eye-catching visuals and a steady rollout of essential concepts, including an algorithm analysis to classify the performance of every algorithm presented in the book. At the end of each chapter, you'll get to apply what you've learned to a novel challenge problem -- simulating the experience you might find in a technical code interview.With this book, you will:Examine fundamental algorithms central to computer science and software engineeringLearn common strategies for efficient problem solving -- such as divide and conquer, dynamic programming, and greedy approachesAnalyze code to evaluate time complexity using big O notationUse existing Python libraries and data structures to solve problems using algorithmsUnderstand the main steps of important algorithms
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Distributed Algorithms
This volume contains the proceedings of the 4th International Workshop on Distributed Algorithms, held near Bari, Italy, September 24-26, 1990. The workshop was a forum for researchers, students and other interested persons to discuss recent results and trends in the design and analysis of distributed algorithms for communication networks and decentralized systems. The volume includes all 28 papers presented at the workshop, covering current research in such aspects of distributed algorithm design as distributed combinatorial algorithms, distributed algorithms on graphs, distributed algorithms for new types of decentralized systems, distributed data structures, synchronization and load-balancing, distributed algorithms for control and communication, design and verification of network protocols, routing algorithms, fail-safe and fault-tolerant distributed algorithms, distributed database techniques, algorithms for transaction management and replica control, and other related topics.
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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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Nature-Inspired Algorithms for Big Data Frameworks
As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.
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Frontiers in Algorithmics and Algorithmic Aspects in Information and Management
This book constitutes the refereed proceedings of the 6th International Frontiers of Algorithmics Workshop, FAW 2012, and the 8th International Conference on Algorithmic Aspects in Information and Management, AAIM 2012, jointly held in Beijing, China, in May 2012. The 33 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on algorithms and data structures, algorithmic game theory and incentive analysis, biomedical imaging algorithms, communication networks and optimization, computational learning theory, knowledge discovery, and data mining, experimental algorithmic methodologies, optimization algorithms in economic and operations research, pattern recognition algorithms and trustworthy algorithms and trustworthy software.
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Algorithms and Architectures for Parallel Processing
This book constitutes the proceedings of the 17th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2017, held in Helsinki, Finland, in August 2017.The 25 full papers presented were carefully reviewed and selected from 117 submissions. They cover topics such as parallel and distributed architectures; software systems and programming models; distributed and network-based computing; big data and its applications; parallel and distributed algorithms; applications of parallel and distributed computing; service dependability and security in distributed and parallel systems; service dependability and security in distributed and parallel systems; performance modeling and evaluation.This volume also includes 41 papers of four workshops, namely: the 4th International Workshop on Data, Text, Web, and Social Network Mining (DTWSM 2017), the 5th International Workshop on Parallelism in Bioinformatics (PBio 2017), the First International Workshop on Distributed Autonomous Computing in Smart City (DACSC 2017), and the Second International Workshop on Ultrascale Computing for Early Researchers (UCER 2017).
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Introduction to Algorithms for Data Mining and Machine Learning
Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.
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Design and Analysis of Algorithms
These are my lecture notes from CS681: Design and Analysis of Algo rithms, a one-semester graduate course I taught at Cornell for three consec utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts • A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. • M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. • R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references.
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Algorithms and Complexity
Here are the refereed proceedings of the 6th Italian Conference on Algorithms and Computation, CIAC 2006. The 33 revised full papers presented together with 3 invited papers address such topics as sequential, parallel and distributed algorithms, data structures, approximation algorithms, randomized algorithms, on-line algorithms, graph algorithms, analysis of algorithms, algorithm engineering, algorithmic game theory, computational biology, computational complexity, communication networks, computational geometry, cryptography, discrete optimization, graph drawing, mathematical programming, and quantum algorithms.
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Data Structures for Raster Graphics
Raster graphics differs from the more traditional vector or line graphics in the sense that images are not made up from line segments but from discrete elements orderly arranged in a two-dimensional rectangular region. There are two reasons for the growing popularity of raster graphics or bit-mapped displays: I) the possibilities they offer to show extremely realistic pictures 2) the dropping prices of those displays and associated processors and memories. With the rise of raster graphics, all kinds of new techniques, methods, algorithms and data representations are associated -such as ray tracing, raster operations, and quadtrees-bringing with them a lot of fruitful research. As stated above raster graphics allows to create extremely realistic (synthesized) pictures. There are important applications in such diverse areas as industrial deSign, flight Simulation, education, image processing and animation. Unfortunately many applications are hampered by the fact that with the present state of the art they reqUire an excessive amount of computing resources. Hence it is worthwhile to investigate methods and techniques which may be of help in redudng computer costs associated with raster graphics applications. Since the choice of data srtuc tures influences the efficiency of algorithms in a crudal way, a workshop was set up in order to bring together a (limited) number of experienced researchers to dis cuss this topic. The workshop was held from 24 to 28 June 1985 at Steensel, a tiny village in the neighbourhood of Eindhoven, the Netherlands.
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Machine Vision Algorithms in Java
This book presents key machine vision techniques and algorithms, along with the associated Java source code. Special features include a complete self-contained treatment of all topics and techniques essential to the understanding and implementation of machine vision; an introduction to object-oriented programming and to the Java programming language, with particular reference to its imaging capabilities; Java source code for a wide range of real-world image processing and analysis functions; an introduction to the Java 2D imaging and Java Advanced Imaging (JAI) API; and a wide range of illustrative examples.
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Algorithms –- ESA 2012
This book constitutes the refereed proceedings of the 20th Annual European Symposium on Algorithms, ESA 2012, held in Ljubljana, Slovenia, in September 2012 in the context of the combined conference ALGO 2012. The 69 revised full papers presented were carefully reviewed and selected from 285 initial submissions: 56 out of 231 in track design and analysis and 13 out of 54 in track engineering and applications. The papers are organized in topical sections such as algorithm engineering; algorithmic aspects of networks; algorithmic game theory; approximation algorithms; computational biology; computational finance; computational geometry; combinatorial optimization; data compression; data structures; databases and information retrieval; distributed and parallel computing; graph algorithms; hierarchical memories; heuristics and meta-heuristics; mathematical programming; mobile computing; on-line algorithms; parameterized complexity; pattern matching, quantum computing; randomized algorithms; scheduling and resource allocation problems; streaming algorithms.
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Combinatorial Algorithms
This book constitutes the thoroughly refereedpost-workshop proceedings for the 26 International Workshop on combinatorialAlgorithms, IWOCA 2015, held in Verona, Italy, in October 2015.The 29 revised full papers presented were carefullyreviewed and selected from a total of 90 submissions. The topics of the papersinclude algorithms and data structures (including sequential, parallel,distributed, approximation, probabilistic, randomised, and on-line algorithms),algorithms on strings and graphs; applications (bioinformatics, music analysis,networking, and others); combinatorics on words; combinatorial enumeration;combinatorial optimization; complexity theory; computational biology;compression and information retrieval; cryptography and information security;decompositions and combinatorial designs; discrete and computational geometry;graph drawing and labeling; graph theory.
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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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Algorithms – ESA 2005
This volume contains the 75 contributed papers and the abstracts of the three invited lectures presented at the 13th Annual European Symposium on Al- rithms (ESA 2005), held in Palma de Mallorca, Spain, October 3-6, 2005. The threedistinguishedinvitedspeakerswereGiuseppeF.Italiano,CristopherMoore and Joseph (Se?) Naor. Since 2002,ESA has consisted of two tracks, with separate programcomm- tees, which dealt respectively with - the designandmathematicalanalysis ofalgorithms(the "DesignandAna- sis" track); - real-worldapplications, engineering and experimental analysis of algorithms (the "Engineering and Applications" track). Previous ESAs in the current two track format were held in Rome, Italy (2002);Budapest,Hungary(2003);andBergen,Norway(2004).Theproceedings of these symposia were published as Springer's LNCS volumes 2461, 2832, and 3221 respectively. Papers were solicited in all areas of algorithmic research, including but not limited to algorithmic aspects of networks, approximation and on-line al- rithms, computational biology, computational geometry, computational ?nance and algorithmic game theory, data structures, database and information - trieval, external memory algorithms, graph algorithms, graph drawing, machine learning, mobile computing, pattern matching and data compression, quantum computing, and randomized algorithms.The algorithms could be sequential, distributed, or parallel. Submissions were especially encouraged in the area of mathematical programming and operations research, including combinatorial optimization, integer programming, polyhedral combinatorics, and semide?nite programming.
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Nature-Inspired Algorithms for Big Data Frameworks
As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries.Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.
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Algorithms and Order
This volume contains the texts of the principal survey papers presented at ALGORITHMS -and ORDER, held· at Ottawa, Canada from June 1 to June 12, 1987. The conference was supported by grants from the N.A.T.O. Advanced Study Institute programme, the University of Ottawa, and the Natural Sciences and Engineering Research Council of Canada. We are grateful for this considerable support. Over fifty years ago, the Symposium on Lattice Theory, in Charlottesville, U.S.A., proclaimed the vitality of ordered sets. Only twenty years later the Symposium on Partially Ordered Sets and Lattice Theory, held at Monterey, U.S.A., had solved many of the problems that had been originally posed. In 1981, the Symposium on Ordered Sets held at Banff, Canada, continued this tradition. It was marked by a landmark volume containing twenty-three articles on almost all current topics in the theory of ordered sets and its applications. Three years after, Graphs and Orders, also held at Banff, Canada, aimed to document the role of graphs in the theory of ordered sets and its applications. Because of its special place in the landscape of the mathematical sciences order is especially sensitive to new trends and developments. Today, the most important current in the theory and application of order springs from theoretical computer seience. Two themes of computer science lead the way. The first is data structure. Order is common to data structures.
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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
R 2,442.00
Algorithmic Aspects in Information and Management
This book constitutes the refereed proceedings of the 4th International Conference on Algorithmic Aspects in Information and Management, AAIM 2008, held in Shanghai, China, in June 2008. The 30 revised full papers presented together with abstracts of 2 invited talks were carefully reviewed and selected from 53 submissions. The papers cover original algorithmic research on immediate applications and/or fundamental problems pertinent to information management and management science. Topics addressed are: approximation algorithms, geometric data management, biological data management, graph algorithms, computational finance, mechanism design, computational game theory, network optimization, data structures, operations research, discrete optimization, online algorithms, FPT algorithms, and scheduling algorithms.
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Introduction to the Analysis of Algorithms, An
Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth
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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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