Data structures based on non-linear relations and data processing methods, Kai Fan, Xiang Ji, Xingni Zhou, Yanzhuo Ma, Zhiyuan Ren

Автор: Maosong Sun, Xiaojie Wang, Baobao Chang
Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data
ISBN: 3319690043 ISBN-13(EAN): 9783319690049
Издательство: Springer
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Цена: 35330.00 T
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Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.

Автор: Dan Gusfield
Название: Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course
ISBN: 1108421768 ISBN-13(EAN): 9781108421768
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.

Автор: Steven Bell, Jing Pu, James Hegarty, Mark Horowitz
Название: Compiling Algorithms for Heterogeneous Systems
ISBN: 1681732637 ISBN-13(EAN): 9781681732633
Издательство: Mare Nostrum (Eurospan)
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Цена: 72070.00 T
Наличие на складе: Невозможна поставка.
Описание: Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power. To meet these goals, architects are building increasingly specialized compute engines tailored for these specific tasks. The resulting computer systems are heterogeneous, containing multiple processing cores with wildly different execution models. Unfortunately, the cost of producing this specialized hardware—and the software to control it—is astronomical. Moreover, the task of porting algorithms to these heterogeneous machines typically requires that the algorithm be partitioned across the machine and rewritten for each specific architecture, which is time consuming and prone to error.Over the last several years, the authors have approached this problem using domain-specific languages (DSLs): high-level programming languages customized for specific domains, such as database manipulation, machine learning, or image processing. By giving up generality, these languages are able to provide high-level abstractions to the developer while producing high performance output. The purpose of this book is to spur the adoption and the creation of domain-specific languages, especially for the task of creating hardware designs.In the first chapter, a short historical journey explains the forces driving computer architecture today. Chapter 2 describes the various methods for producing designs for accelerators, outlining the push for more abstraction and the tools that enable designers to work at a higher conceptual level. From there, Chapter 3 provides a brief introduction to image processing algorithms and hardware design patterns for implementing them. Chapters 4 and 5 describe and compare Darkroom and Halide, two domain-specific languages created for image processing that produce high-performance designs for both FPGAs and CPUs from the same source code, enabling rapid design cycles and quick porting of algorithms. The final section describes how the DSL approach also simplifies the problem of interfacing between application code and the accelerator by generating the driver stack in addition to the accelerator configuration.This book should serve as a useful introduction to domain-specialized computing for computer architecture students and as a primer on domain-specific languages and image processing hardware for those with more experience in the field.

Автор: Damir Gainanov
Название: Graphs for Pattern Recognition: Infeasible Systems of Linear Inequalities
ISBN: 3110480131 ISBN-13(EAN): 9783110480139
Издательство: Walter de Gruyter
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Цена: 123910.00 T
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Описание: This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition.Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology.The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: PrefacePattern recognition, infeasible systems of linear inequalities, and graphsInfeasible monotone systems of constraintsComplexes, (hyper)graphs, and inequality systemsPolytopes, positive bases, and inequality systemsMonotone Boolean functions, complexes, graphs, and inequality systemsInequality systems, committees, (hyper)graphs, and alternative coversBibliographyList of notationIndex

Автор: Emmanouil Amolochitis
Название: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining
ISBN: 8793609647 ISBN-13(EAN): 9788793609648
Издательство: Taylor&Francis
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Цена: 78590.00 T
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Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.

Автор: Zhang Tsinghua University Press Liyi
Название: Blind Equalization in Neural Networks
ISBN: 3110449625 ISBN-13(EAN): 9783110449624
Издательство: Walter de Gruyter
Цена: 123910.00 T
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Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.

Автор: Andrade
Название: Fundamentals of Stream Processing
ISBN: 1107015545 ISBN-13(EAN): 9781107015548
Издательство: Cambridge Academ
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Цена: 91870.00 T
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Описание: This book teaches fundamentals of the stream processing paradigm that addresses performance, scalability and usability challenges in extracting insights from massive amounts of live, streaming data. It presents core principles behind application design, system infrastructure and analytics, coupled with real-world examples for a comprehensive understanding of the stream processing area.

Автор: Hassanieh Haitham
Название: The Sparse Fourier Transform
ISBN: 1947487043 ISBN-13(EAN): 9781947487048
Издательство: Mare Nostrum (Eurospan)
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Цена: 69010.00 T
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Описание: The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary.This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits.This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.

Автор: Ji Xiang, Kai Fan, Xingni Zhou, Yanzhuo Ma, zhiyuan Ren
Название: [Set Data Structures and Algorithms Analysis, Vol 1+2]
ISBN: 311068165X ISBN-13(EAN): 9783110681659
Издательство: Walter de Gruyter
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Цена: 128870.00 T
Наличие на складе: Нет в наличии.
Описание:

The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.

Автор: Agarwal, Dr Basant, Baka, Benjamin
Название: Hands-On Data Structures and Algorithms with Python 2 ed
ISBN: 1788995570 ISBN-13(EAN): 9781788995573
Издательство: Неизвестно
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Цена: 53940.00 T
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Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.

Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang
Название: Data structures based on linear relations
ISBN: 3110595575 ISBN-13(EAN): 9783110595574
Издательство: Walter de Gruyter
Цена: 80520.00 T
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Описание:

Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.

Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang
Название: Non-linear Data Structures and Data Processing
ISBN: 3110676052 ISBN-13(EAN): 9783110676051
Издательство: Walter de Gruyter
Цена: 80520.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.