Machine Learning Algorithms for Problem Solving in Computational Applications

The wonder of being a dad is on display in this touching tribute to fathers. After all, the connection between a father and child yields a lifetime of learning and love. In You and Me, Me and You, tha

在全球化已成日常的工作環境中，管理者必須具備跨文化理解與行動能力。本書第三版以「所有管理者都是全球管理者」為前提，重新梳理跨文化管理的理論與實踐。作者不僅介紹主要文化模型，也深入探討領導、溝通與倫理在不同文化脈絡中的差異與調適方式。更新後的內容更貼近現實職場，透過真實案例與具體策略，協助讀者面對國際指派、跨國團隊與多元勞動力的挑戰。語言清楚、結構明確，是學生建立基礎視野、也是專業人士精進能力的重要讀本。The third edition of this popular textbook has been thoroughly expanded and updated throughout to explore the latest approaches to cross-cultural management, presenting strategies and tactics for managing international assignments and global teams. With a clear emphasis on learning and development, this new edition introduces a global management model, along with enhanced 'Applications' and 'Manager's Notebooks', to encourage students to acquire skills in multicultural competence that will be highly valued by their future employers. These skills have never been more important, in a world where, increasingly, all managers are global managers and where management practices and processes can differ significantly across national and regional boundaries. This textbook is suitable for student

本書講述兩個形影不離的好朋友 Frank 和 Harold，做什麼事都要一起。來到熱鬧的遊樂園，他們最期待的就是搭乘雲霄飛車，卻在入口被現實攔下——其中一個不夠高。規則擺在眼前，失望一度出現，但這對好朋友沒有放棄。他們動腦想辦法，試著用創意與合作解決問題。故事節奏明快，畫面充滿動感，翻頁之間像雲霄飛車般起伏。由Steven Weinberg以誇張線條與亮眼色彩呈現，幽默又貼近孩子的情緒。結尾的巧思帶來驚喜，也輕輕提醒讀者：真正的朋友，會一起想辦法，而不是留下誰。Two friends—one short and one tall—must come up with a plan to overcome a serious height restriction so they can ride a roller coaster together in this delightfully cheeky and bright picture book from the author ofRex Finds an Egg! Egg! Egg!Best friends Frank and Harold do everything as a pair. And at the fair, they want to ride the roller coaster together, too! But one of them isn’t tall enough.Can this energetic duo think outside the box and figure out a way to overcome the height restriction and ride the roller coaster? Find out in this adorable picture book that celebrates the value of friendship and encourages problem solving from Steven Weinberg.

Fans of Tad Hills’s Duck & Goose books will feel right at home with A Friend for Bo, the story of a little rabbit who makes a new friend named Rollie! The only problem is that Rollie doesn’t l

Get ready to lift the flaps, giggle, and discover a rainbow of fun! In this interactive call-and-response book, young children are invited to lift the flaps to reveal the answers about the colors of some of their favorite things. From pink chocolate cake to green clouds, and even zebras with polka dots, the silly suggestions will have kids laughing out loud while learning all about colors.• A visual play-and-learn adventure that stimulates early learning and encourages creativity• An irresistible introduction to the basic concept of colors• Sturdy board book design with 16 big flaps that's just right for little handsWith its big flaps, Lift and Play: Colors is a lively introduction to the world of colors that children will turn to again and again!• Great family read-aloud book• Books for 3–5 years old• Books for preschool and kindergarten children

First book-length reference collection of research examining the unique opportunities and challenges presented by task-based language learning and teaching in Asia.

Covering the essential math concepts learned in the first years of school, Amazing Visual Math brings a whole new dimension to learning. Amazing Visual Math is an interactive hands-on experience that

A sinister Problem has occurred in London: all nature of ghosts, haunts, spirits, and specters are appearing throughout the city, and they aren't exactly friendly. Only young people have the psychic abilities required to see?and eradicate?these supernatural foes. Many different Psychic Detection Agencies have cropped up to handle the dangerous work, and they are in fierce competition for business. In The Screaming Staircase, the plucky and talented Lucy Carlyle teams up with Anthony Lockwood, the charismatic leader of Lockwood & Co, a small agency that runs independent of any adult supervision. After an assignment leads to both a grisly discovery and a disastrous end, Lucy, Anthony, and their sarcastic colleague, George, are forced to take part in the perilous investigation of Combe Carey Hall, one of the most haunted houses in England. Will Lockwood & Co. survive the Hall’s legendary Screaming Staircase and Red Room to see another day? Readers who enjoyed the action, suspense,

Learning to Emulate the Wise is the first book of a three-volume series that constructs a historically informed, multidisciplinary framework to examine how traditional Chinese knowledge systems and gr

A bright and engaging first information book about farms, specially designed for children learning to read.FARM unlocks a free 16-page digital companion book, FARM FUN, offering even more information,

The essays in this volume grew from a series of talks delivered in late 2010 as the Liang Qichao Memorial Lectures at the Academy of National Learning (Guoxue yuan) of Tsinghua University, Beijing.Off

A money-saving CISSP boxed set from the #1 name in IT security certification and trainingCISSP Boxed Set bundles Shon Harris’ bestselling CISSP All-in-One Exam Guide, Fifth Edition and CISSP Practice Exams with a bonus, second CD-ROM featuring all-new training material—all at a discount of 12% off MSRP. CISSP All-in-One Exam Guide, Fifth Edition provides a comprehensive and in-depth exam review and self-study system covering all ten CISSP domains. The book includes exam tips that highlight actual exam topics, technical discussion sidebars, and hands-on examples and exercises that support practical learning for real-world situations. The CD-ROM contains practice exam questions, a video training excerpt, and an e-book. CISSP Practice Exams reinforces what is taught in the Exam Guide with questions for review organized by exam domain and more than 1000 additional questions available online. A bonus CD-ROM available only with this Boxed Set features two additional practice exams as well as

Out on the playground, kids are skipping rope and making trades. In the library, they’re whispering, fi dgeting, and giggling. In the classroom, they’re learning their lessons....or spinning tales abo

For the Seven Oaks friends, there is always something to do. Whether they're singing along with Pokey Porcupine's harmonica or playing soccer with Jumper Rabbit, everyone is having fun and learning a

At last, here is a picture book about the Good Knight and his three little dragon friends, the stars of Dutton's best-loved Easy Readers. The old wizard has asked the dragons to take care of his cats for a few days. There's just one problem: they can't read the wizard's instructions! The dragons make their best guesses. They take the cats swimming and camping, with hilarious results. Of course, it's up to the Good Knight to come to the rescue in his funniest outing yet.Good Night, Good Knight was an ALA Notable Book and a Booklist Top 10 Easy Reader, among other honors.

This enthusiastic introduction to the fundamentals of information theory builds from classical Shannon theory through to modern applications in statistical learning. Includes over 210 student exercises, emphasising practical applications in statistics, machine learning and modern communication theory. Accompanied by online instructor solutions.

Recovering the phase of the Fourier transform is a ubiquitous problem in imaging applications from astronomy to nanoscale X-ray diffraction imaging. Despite the efforts of a multitude of scientists, from astronomers to mathematicians, there is, as yet, no satisfactory theoretical or algorithmic solution to this class of problems. Written for mathematicians, physicists and engineers working in image analysis and reconstruction, this book introduces a conceptual, geometric framework for the analysis of these problems, leading to a deeper understanding of the essential, algorithmically independent, difficulty of their solutions. Using this framework, the book studies standard algorithms and a range of theoretical issues in phase retrieval and provides several new algorithms and approaches to this problem with the potential to improve the reconstructed images. The book is lavishly illustrated with the results of numerous numerical experiments that motivate the theoretical development and p

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the ne

The study of complex variables is beautiful from a purely mathematical point of view, and very useful for solving a wide array of problems arising in applications. This introduction to complex variables, suitable as a text for a one-semester course, has been written for undergraduate students in applied mathematics, science, and engineering. Based on the authors' extensive teaching experience, it covers topics of keen interest to these students, including ordinary differential equations, as well as Fourier and Laplace transform methods for solving partial differential equations arising in physical applications. Many worked examples, applications, and exercises are included. With this foundation, students can progress beyond the standard course and explore a range of additional topics, including generalized Cauchy theorem, Painlevé equations, computational methods, and conformal mapping with circular arcs. Advanced topics are labeled with an asterisk and can be included in the syllabus

The world of machine learning is changing all the time. It is so amazing the idea that we are able to take a computer and let it learn as it goes. Without having to write out all of the codes that we need for every situation out there or every input that the user may pick, we are able to write out codes in machine learning, even with Python, in order to let the computer or device learn and make decisions on its own.This guidebook is going to take a closer look at how Python machine learning is able to work, as well as how you can use some of the tools and techniques that come with this process for your own needs. When you are interested in learning more about what machine learning is all about, as well as how you can use a part of the coding from Python inside of this process, then this guidebook is the tool for you Some of the topics that we will explore when we go through this guidebook will include: Understanding some of the basics of machine learning;Some of the different parts tha

This innovative book models pollution mitigation as a negative externality whilst also providing desirable and useful solutions, such as establishing the triangular equivalence relationship among the Lindahl equilibrium without transfers, the Nash bargaining solution with the payoffs of the Cournot-Nash equilibrium as the status quo point, and the social optimum under the Lindahl weights. By introducing programming algorithms to validate these relationships numerically, Zili Yang bridges the gap between analytical results and empirical modelling, ultimately solving the Lindahl equilibrium and hybrid Nash equilibria in the influential RICE model. This text demonstrates the complexity and variety of environment externality problems, ranging from mixed externality to correlated externalities to environmental externality under IRS and policy applications. Integrating theory, algorithms and applications in a comprehensive framework, The Environment and Externality will benefit scholars and

This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples. Concepts are reinforced with hands-on exercises to nurture the student's skill in problem solving. New concepts and algorithms are framed by real-world context and established as part of the big picture introduced in an early chapter. A problem-solving strategy is employed in several chapters to equip students with an approach for new problems in pattern recognition. This text also points out common errors that a new player in pattern recognition may encounter, and fosters the ability for readers to find useful resources and independently solve a new pattern recognition task through various working examples. Students with an undergraduate understanding of mathematical analysis, linear algebra, an

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramificatio

Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers.

Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this book summarizes recent developments in the non-asymptotic and asymptotic theory of variational Bayesian learning and suggests how this theory can be applied in practice. The authors begin by developing a basic framework with a focus on conjugacy, which enables the reader to derive tractable algorithms. Next, it summarizes non-asymptotic theory, which, although limited in application to bilinear models, precisely describes the behavior of the variational Bayesian solution and reveals its sparsity inducing mechanism. Finally, the text summarizes asymptotic theory, which reveals phase transition phenomena depending on the prior setting, thus providing suggestions on how to set hyperparameters for particular purposes. Detailed derivations allow readers to follow along without prior knowledge of the mathematical techniques specific to

Based on time-tested course material, this authoritative text examines the key topics, advanced mathematical concepts, and novel analytical tools needed to understand modern communication and radar systems. It covers computational linear algebra theory, VLSI systolic algorithms and designs, practical aspects of chaos theory, and applications in beamforming and array processing, and uses a variety of CDMA codes, as well as acoustic sensing and beamforming algorithms to illustrate key concepts. Classical topics such as spectral analysis are also covered, and each chapter includes a wealth of homework problems. This is an invaluable text for graduate students in electrical and computer engineering, and an essential reference for practitioners in communications and radar engineering.

This book presents recent research on computational intelligence (CI) algorithms in the field of sport. In the modern age, information technologies have greatly reduced the need for human effort in th

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts a

This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finan

Based on the first Workshop for Women in Computational Topology that took place in 2016, this volume assembles new research and applications in computational topology. Featured articles range ov

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform gener

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that

This book covers all the relevant dictionary learning algorithms, presenting them in full detail and showing their distinct characteristics while also revealing the similarities. It gives implementati

This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together

The latest advances in computational methods have increased their scalability across a diverse range of applications and possible practical deployment. This book outlines the key emerging trends in co

This textbook explains the principles of fuzzy systems in some depth together with information useful in realizing them within computational processes. The various algorithms and example problem solut

The wildly popular author of Bad Arguments returns with a funny, smart introduction to algorithms--those perennially misunderstood, increasingly important problem-solving rules that can save you time

This book introduces polyhedra as a tool for graph theory and discusses their properties and applications in solving the Gauss crossing problem. The discussion is extended to embeddings on manifolds,

This package contains Problem Solving with C++, 8e, Student Value Edition, an access card for MyProgrammingLab, and a Pearson eText Student Access Code Card forProblem Solving with C++