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Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

This textbook intends to be a comprehensive and substantially self-contained two-volume book covering performance reliability and availability evaluation subjects. The volumes focus on computing systems although the methods may also be applied to other systems. The first volume covers Chapter 1 to Chapter 14 whose subtitle is ``Performance Modeling and Background. The second volume encompasses Chapter 15 to Chapter 25 and has the subtitle ``Reliability and Availability Modeling Measuring and Workload and Lifetime Data Analysis. This text is helpful for computer performance professionals for supporting planning design configuring and tuning the performance reliability and availability of computing systems. Such professionals may use these volumes to get acquainted with specific subjects by looking at the particular chapters. Many examples in the textbook on computing systems will help them understand the concepts covered in each chapter. The text may also be helpful for the instructor who teaches performance reliability and availability evaluation subjects. Many possible threads could be configured according to the interest of the audience and the duration of the course. Chapter 1 presents a good number of possible courses programs that could be organized using this text. Volume I is composed of the first two parts besides Chapter 1. Part I gives the knowledge required for the subsequent parts of the text. This part includes six chapters. It covers an introduction to probability descriptive statistics and exploratory data analysis random variables moments covariance some helpful discrete and continuous random variables Taylor series inference methods distribution fitting regression interpolation data scaling distance measures and some clustering methods. Part II presents methods for performance evaluation modeling such as operational analysis Discrete-Time Markov Chains (DTMC) and Continuous Time Markov Chains (CTMC) Markovian queues Stochastic Petri nets (SPN) and discrete event simulation. | Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

GBP 120.00
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Choreomata Performance and Performativity after AI

Choreomata Performance and Performativity after AI

Is artificial intelligence (AI) becoming more and more expressive or is human thought adopting more and more structures from computation? What does it mean to perform oneself through AI or to construct one’s subjectivity through AI? How does AI continue to complicate what it means to have a body? Has the golden age of AI especially with regards to creative applications already ended? Choreomata: Performance and Performativity after AI is a book about performance and performativity but more specifically it is a book about the performance of artificiality and the performance of intelligence. Both humans and human-designed computational forces are thoroughly engaged in an entangled mutual performance of AI. Choreomata spins up a latticework of interdisciplinary thought pairing theoretical inquiry from philosophy information theory and computer science with practical case studies from visual art dance music and social theory. Through cross-disciplinary proportions and a diverse roster of contributors this book contains insights for computer scientists social scientists industry professionals artists and beyond. | Choreomata Performance and Performativity after AI

GBP 44.99
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High Performance Computing Programming and Applications

High Performance Computing Programming and Applications

High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achieving high performance. Even though the text concentrates on C and Fortran the techniques described can be applied to other languages such as C++ and Java. Drawing on their experience with chips from AMD and systems interconnects and software from Cray Inc. the authors explore the problems that create bottlenecks in attaining good performance. They cover techniques that pertain to each of the three levels of parallelism: Message passing between the nodes Shared memory parallelism on the nodes or the multiple instruction multiple data (MIMD) units on the accelerator Vectorization on the inner level After discussing architectural and software challenges the book outlines a strategy for porting and optimizing an existing application to a large massively parallel processor (MPP) system. With a look toward the future it also introduces the use of general purpose graphics processing units (GPGPUs) for carrying out HPC computations. A companion website at www. hybridmulticoreoptimization. com contains all the examples from the book along with updated timing results on the latest released processors. | High Performance Computing Programming and Applications

GBP 59.99
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Mathematics and Music Composition Perception and Performance

Mathematics and Music Composition Perception and Performance

Mathematics and Music: Composition Perception and Performance Second Edition includes many new sections and more consistent expectations of a student’s experience. The new edition of this popular text is more accessible for students with limited musical backgrounds and only high school mathematics is required. The new edition includes more illustrations than the previous one and the added sections deal with the XronoMorph rhythm generator musical composition and analyzing personal performance. The text teaches the basics of reading music explaining how various patterns in music can be described with mathematics providing mathematical explanations for musical scales harmony and rhythm. The book gives students a deeper appreciation showing how music is informed by both its mathematical and aesthetic structures. Highlights of the Second Edition: Now updated for more consistent expectations of students’ backgrounds More accessible for students with limited musical backgrounds Full-color presentation Includes more thorough coverage of spectrograms for analyzing recorded music Provides a basic introduction to reading music Features new coverage of building and evaluating rhythms | Mathematics and Music Composition Perception and Performance

GBP 42.99
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Performance Analysis of Queuing and Computer Networks

Performance Analysis of Queuing and Computer Networks

Performance Analysis of Queuing and Computer Networks develops simple models and analytical methods from first principles to evaluate performance metrics of various configurations of computer systems and networks. It presents many concepts and results of probability theory and stochastic processes. After an introduction to queues in computer networks this self-contained book covers important random variables such as Pareto and Poisson that constitute models for arrival and service disciplines. It then deals with the equilibrium M/M/1/∞queue which is the simplest queue that is amenable for analysis. Subsequent chapters explore applications of continuous time state-dependent single Markovian queues the M/G/1 system and discrete time queues in computer networks. The author then proceeds to study networks of queues with exponential servers and Poisson external arrivals as well as the G/M/1 queue and Pareto interarrival times in a G/M/1 queue. The last two chapters analyze bursty self-similar traffic and fluid flow models and their effects on queues.

GBP 59.99
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Parallel Programming for Modern High Performance Computing Systems

Parallel Programming for Modern High Performance Computing Systems

In view of the growing presence and popularity of multicore and manycore processors accelerators and coprocessors as well as clusters using such computing devices the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today These include multicore CPUs manycore (co)processors such as Intel Xeon Phi accelerators such as GPUs and clusters as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms such as master-slave geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed including MPI OpenMP Pthreads CUDA OpenCL and OpenACC. It also demonstrates through selected code listings how selected APIs can be used to implement important programming paradigms. Furthermore it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources and it shows how to use modern elements of these APIs. Selected optimization techniques are also included such as overlapping communication and computations implemented using various APIs. Features:Discusses the popular and currently available computing devices and cluster systemsIncludes typical paradigms used in parallel programsExplores popular APIs for programming parallel applicationsProvides code templates that can be used for implementation of paradigmsProvides hybrid code examples allowing multi-level parallelizationCovers the optimization of parallel programs

GBP 44.99
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Computer Systems Architecture

Computer Systems Architecture

Computer Systems Architecture provides IT professionals and students with the necessary understanding of computer hardware. It addresses the ongoing issues related to computer hardware and discusses the solutions supplied by the industry. The book describes trends in computing solutions that led to the current available infrastructures tracing the initial need for computers to recent concepts such as the Internet of Things. It covers computers’ data representation explains how computer architecture and its underlying meaning changed over the years and examines the implementations and performance enhancements of the central processing unit (CPU). It then discusses the organization hierarchy and performance considerations of computer memory as applied by the operating system and illustrates how cache memory significantly improves performance. The author proceeds to explore the bus system algorithms for ensuring data integrity input and output (I/O) components methods for performing I/O various aspects relevant to software engineering and nonvolatile storage devices such as hard drives and technologies for enhancing performance and reliability. He also describes virtualization and cloud computing and the emergence of software-based systems’ architectures. Accessible to software engineers and developers as well as students in IT disciplines this book enhances readers’ understanding of the hardware infrastructure used in software engineering projects. It enables readers to better optimize system usage by focusing on the principles used in hardware systems design and the methods for enhancing performance.

GBP 44.99
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Embedded and Networking Systems Design Software and Implementation

Embedded and Networking Systems Design Software and Implementation

Embedded and Networking Systems: Design Software and Implementation explores issues related to the design and synthesis of high-performance embedded computer systems and networks. The emphasis is on the fundamental concepts and analytical techniques that are applicable to a range of embedded and networking applications rather than on specific embedded architectures software development or system-level integration. This system point of view guides designers in dealing with the trade-offs to optimize performance power cost and other system-level non-functional requirements. The book brings together contributions by researchers and experts from around the world offering a global view of the latest research and development in embedded and networking systems. Chapters highlight the evolution and trends in the field and supply a fundamental and analytical understanding of some underlying technologies. Topics include the co-design of embedded systems code optimization for a variety of applications power and performance trade-offs benchmarks for evaluating embedded systems and their components and mobile sensor network systems. The book also looks at novel applications such as mobile sensor systems and video networks. A comprehensive review of groundbreaking technology and applications this book is a timely resource for system designers researchers and students interested in the possibilities of embedded and networking systems. It gives readers a better understanding of an emerging technology evolution that is helping drive telecommunications into the next decade. | Embedded and Networking Systems Design Software and Implementation

GBP 77.99
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Parallel Algorithms

Parallel Algorithms

Focusing on algorithms for distributed-memory parallel architectures Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation parallel algorithm design for homogeneous and heterogeneous platforms complexity and performance analysis and essential notions of scheduling. The book extracts fundamental ideas and algorithmic principles from the mass of parallel algorithm expertise and practical implementations developed over the last few decades. In the first section of the text the authors cover two classical theoretical models of parallel computation (PRAMs and sorting networks) describe network models for topology and performance and define several classical communication primitives. The next part deals with parallel algorithms on ring and grid logical topologies as well as the issue of load balancing on heterogeneous computing platforms. The final section presents basic results and approaches for common scheduling problems that arise when developing parallel algorithms. It also discusses advanced scheduling topics such as divisible load scheduling and steady-state scheduling. With numerous examples and exercises in each chapter this text encompasses both the theoretical foundations of parallel algorithms and practical parallel algorithm design.

GBP 44.99
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Empirical Bayes Methods with Applications

Empirical Bayes Methods with Applications

The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. A chapter is devoted to a discussion of alternatives to the empirical Bayes approach and there is also a chapter giving details of several actual applications of empirical Bayes method. | Empirical Bayes Methods with Applications

GBP 180.00
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Structured Credit Portfolio Analysis Baskets and CDOs

Structured Credit Portfolio Analysis Baskets and CDOs

The financial industry is swamped by credit products whose economic performance is linked to the performance of some underlying portfolio of credit-risky instruments like loans bonds swaps or asset-backed securities. Financial institutions continuously use these products for tailor-made long and short positions in credit risks. Based on a steadily growing market there is a high demand for concepts and techniques applicable to the evaluation of structured credit products. Written from the perspective of practitioners who apply mathematical concepts to structured credit products Structured Credit Portfolio Analysis Baskets & CDOs starts with a brief wrap-up on basic concepts of credit risk modeling and then quickly moves on to more advanced topics such as the modeling and evaluation of basket products credit-linked notes referenced to credit portfolios collateralized debt obligations and index tranches. The text is written in a self-contained style so readers with a basic understanding of probability will have no difficulties following it. In addition many examples and calculations have been included to keep the discussion close to business applications. Practitioners as well as academics will find ideas and tools in the book that they can use for their daily work. | Structured Credit Portfolio Analysis Baskets and CDOs

GBP 59.99
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Introduction to Computational Models with Python

Introduction to Computational Models with Python

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website. The book’s five sections present: An overview of problem solving and simple Python programs introducing the basic models and techniques for designing and implementing problem solutions independent of software and hardware toolsProgramming principles with the Python programming language covering basic programming concepts data definitions programming structures with flowcharts and pseudo-code solving problems and algorithmsPython lists arrays basic data structures object orientation linked lists recursion and running programs under LinuxImplementation of computational models with Python using Numpy with examples and case studies The modeling of linear optimization problems from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing including parallel computing using MPI grid computing and other methods and techniques used in high-performance computing.

GBP 44.99
1

Medical Risk Prediction Models With Ties to Machine Learning

Medical Risk Prediction Models With Ties to Machine Learning

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians epidemiologists and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk calculator from scratch Discrimination calibration and predictive performance with censored data and competing risks R-code and illustrative examples Interpretation of prediction performance via benchmarks Comparison and combination of rival modeling strategies via cross-validation Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years. Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research. | Medical Risk Prediction Models With Ties to Machine Learning

GBP 48.99
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Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas such as game development decision making and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning which is followed by Gaussian process introduction classification regression covariance and performance analysis of Gaussian processes with other models. FEATURES Contains recent advancements in machine learning Highlights applications of machine learning algorithms Offers both quantitative and qualitative research Includes numerous case studies This book is aimed at graduates researchers and professionals in the field of data science and machine learning.

GBP 105.00
1

The Garbage Collection Handbook The Art of Automatic Memory Management

The Garbage Collection Handbook The Art of Automatic Memory Management

Published in 1996 Richard Jones's Garbage Collection was a milestone in the area of automatic memory management. Its widely acclaimed successor The Garbage Collection Handbook: The Art of Automatic Memory Management captured the state of the field in 2012. Modern technology developments have made memory management more challenging interesting and important than ever. This second edition updates the handbook bringing together a wealth of knowledge gathered by automatic memory management researchers and developers over the past sixty years. The authors compare the most important approaches and state-of-the-art techniques in a single accessible framework. The book addresses new challenges to garbage collection made by recent advances in hardware and software. It explores the consequences of these changes for designers and implementers of high performance garbage collectors. Along with simple and traditional algorithms the book covers state-of-the-art parallel incremental concurrent and real-time garbage collection. Algorithms and concepts are often described with pseudocode and illustrations. Features of this edition Provides a complete up-to-date and authoritative sequel to the 1996 and 2012 books Offers thorough coverage of parallel concurrent and real-time garbage collection algorithms Discusses in detail modern high-performance commercial collectors Explains some of the trickier aspects of garbage collection including the interface to the run-time system Over 90 more pages including new chapters on persistence and energy-aware garbage collection Backed by a comprehensive online database of over 3 400 garbage collection-related publications The adoption of garbage collection by almost all modern programming languages makes a thorough understanding of this topic essential for any programmer. This authoritative handbook gives expert insight on how different collectors work as well as the various issues currently facing garbage collectors. Armed with this knowledge programmers can confidently select and configure the many choices of garbage collectors. http://gchandbook. org | The Garbage Collection Handbook The Art of Automatic Memory Management

GBP 59.99
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The Geometry of Musical Rhythm What Makes a Good Rhythm Good? Second Edition

The Geometry of Musical Rhythm What Makes a Good Rhythm Good? Second Edition

The original edition of The Geometry of Musical Rhythm was the first book to provide a systematic and accessible computational geometric analysis of the musical rhythms of the world. It explained how the study of the mathematical properties of musical rhythm generates common mathematical problems that arise in a variety of seemingly disparate fields. The book also introduced the distance approach to phylogenetic analysis and illustrated its application to the study of musical rhythm. The new edition retains all of this while also adding 100 pages 93 figures 225 new references and six new chapters covering topics such as meter and metric complexity rhythmic grouping expressive timbre and timing in rhythmic performance and evolution phylogenetic analysis of ancient Greek paeonic rhythms. In addition further context is provided to give the reader a fuller and richer insight into the historical connections between music and mathematics. | The Geometry of Musical Rhythm What Makes a Good Rhythm Good? Second Edition

GBP 48.99
1

Image and Video Compression Fundamentals Techniques and Applications

Image and Video Compression Fundamentals Techniques and Applications

Image and video signals require large transmission bandwidth and storage leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus efficient image and video compression algorithms play a significant role in the storage and transmission of data. Image and Video Compression: Fundamentals Techniques and Applications explains the major techniques for image and video compression and demonstrates their practical implementation using MATLAB® programs. Designed for students researchers and practicing engineers the book presents both basic principles and real practical applications. In an accessible way the book covers basic schemes for image and video compression including lossless techniques and wavelet- and vector quantization-based image compression and digital video compression. The MATLAB programs enable readers to gain hands-on experience with the techniques. The authors provide quality metrics used to evaluate the performance of the compression algorithms. They also introduce the modern technique of compressed sensing which retains the most important part of the signal while it is being sensed. | Image and Video Compression Fundamentals Techniques and Applications

GBP 59.99
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Applied Computer Vision and Soft Computing with Interpretable AI

Applied Computer Vision and Soft Computing with Interpretable AI

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: Covers a variety of deep learning architectures useful for computer vision tasks Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable adaptive and optimized solution to a given problem Addresses the different issues and further research opportunities in computer vision and soft computing Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain Considers recent real word problems and the prospective solutions to these problems This book will be useful to researchers students faculty and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks. | Applied Computer Vision and Soft Computing with Interpretable AI

GBP 89.99
1

Data Science for Wind Energy

Data Science for Wind Energy

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications near-ground wind field analysis and forecast turbine power curve fitting and performance analysis turbine reliability assessment and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered including time series models spatio-temporal analysis kernel regression decision trees kNN splines Bayesian inference and importance sampling. More importantly the data science methods are described in the context of wind energy applications with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml. engr. tamu. edu/book-dswe. FeaturesProvides an integral treatment of data science methods and wind energy applicationsIncludes specific demonstration of particular data science methods and their use in the context of addressing wind energy needsPresents real data case studies and computer codes from wind energy research and industrial practiceCovers material based on the author's ten plus years of academic research and insights

GBP 44.99
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Machine Learning Animated

Machine Learning Animated

The release of ChatGPT has kicked off an arms race in Machine Learning (ML) however ML has also been described as a black box and very hard to understand. Machine Learning Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning witnessing AI achieve super-human performance in Atari games such as Breakout Space Invaders Seaquest and Beam Rider. Written in a clear and concise style illustrated with animations and images this book is particularly appealing to readers with no background in computer science mathematics or statistics. Access the book's repository at: https://github. com/markhliu/MLA

GBP 74.99
1

Modern Survey Sampling

Modern Survey Sampling

Starting from the preliminaries and ending with live examples Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems hitting upon possible solutions. The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample’s behavior and assess the elements of discrepancies. Including case studies exercises and solutions the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.

GBP 59.99
1

Concise Encyclopedia of Coding Theory

Concise Encyclopedia of Coding Theory

Most coding theory experts date the origin of the subject with the 1948 publication of A Mathematical Theory of Communication by Claude Shannon. Since then coding theory has grown into a discipline with many practical applications (antennas networks memories) requiring various mathematical techniques from commutative algebra to semi-definite programming to algebraic geometry. Most topics covered in the Concise Encyclopedia of Coding Theory are presented in short sections at an introductory level and progress from basic to advanced level with definitions examples and many references. The book is divided into three parts: Part I fundamentals: cyclic codes skew cyclic codes quasi-cyclic codes self-dual codes codes and designs codes over rings convolutional codes performance bounds Part II families: AG codes group algebra codes few-weight codes Boolean function codes codes over graphs Part III applications: alternative metrics algorithmic techniques interpolation decoding pseudo-random sequences lattices quantum coding space-time codes network coding distributed storage secret-sharing and code-based-cryptography. Features Suitable for students and researchers in a wide range of mathematical disciplines Contains many examples and references Most topics take the reader to the frontiers of research

GBP 74.99
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Basketball Data Science With Applications in R

Basketball Data Science With Applications in R

Using data from one season of NBA games Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots or doing an analysis of the impact of high pressure game situations on the probability of scoring this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge Basketball Data Science with R is suitable for students technicians coaches data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball Presents tools for modelling graphs and figures to visualize the data Includes real world case studies and examples such as estimations of scoring probability using the Golden State Warriors as a test case Provides the source code and data so readers can do their own analyses on NBA teams and players | Basketball Data Science With Applications in R

GBP 48.99
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Numerical Methods for Finance

Numerical Methods for Finance

Featuring international contributors from both industry and academia Numerical Methods for Finance explores new and relevant numerical methods for the solution of practical problems in finance. It is one of the few books entirely devoted to numerical methods as applied to the financial field. Presenting state-of-the-art methods in this area the book first discusses the coherent risk measures theory and how it applies to practical risk management. It then proposes a new method for pricing high-dimensional American options followed by a description of the negative inter-risk diversification effects between credit and market risk. After evaluating counterparty risk for interest rate payoffs the text considers strategies and issues concerning defined contribution pension plans and participating life insurance contracts. It also develops a computationally efficient swaption pricing technology extracts the underlying asset price distribution implied by option prices and proposes a hybrid GARCH model as well as a new affine point process framework. In addition the book examines performance-dependent options variance reduction Value at Risk (VaR) the differential evolution optimizer and put-call-futures parity arbitrage opportunities. Sponsored by DEPFA Bank IDA Ireland and Pioneer Investments this concise and well-illustrated book equips practitioners with the necessary information to make important financial decisions.

GBP 59.99
1

Transfer Learning through Embedding Spaces

Transfer Learning through Embedding Spaces

Recent progress in artificial intelligence (AI) has revolutionized our everyday life. Many AI algorithms have reached human-level performance and AI agents are replacing humans in most professions. It is predicted that this trend will continue and 30% of work activities in 60% of current occupations will be automated. This success however is conditioned on availability of huge annotated datasets to training AI models. Data annotation is a time-consuming and expensive task which still is being performed by human workers. Learning efficiently from less data is a next step for making AI more similar to natural intelligence. Transfer learning has been suggested a remedy to relax the need for data annotation. The core idea in transfer learning is to transfer knowledge across similar tasks and use similarities and previously learned knowledge to learn more efficiently. In this book we provide a brief background on transfer learning and then focus on the idea of transferring knowledge through intermediate embedding spaces. The idea is to couple and relate different learning through embedding spaces that encode task-level relations and similarities. We cover various machine learning scenarios and demonstrate that this idea can be used to overcome challenges of zero-shot learning few-shot learning domain adaptation continual learning lifelong learning and collaborative learning. | Transfer Learning through Embedding Spaces

GBP 44.99
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