Mathematics Books

Book SynopsisThis monograph is devoted to the existence and stability (Ulam-Hyers-Rassias stability and asymptotic stability) of solutions for various classes of functional differential equations or inclusions involving the Hadamard or Hilfer fractional derivative. Some equations present delay which may be finite, infinite, or state-dependent. Others are subject to impulsive effect which may be fixed or non-instantaneous.Readers will find the book self-contained and unified in presentation. It provides the necessary background material required to go further into the subject and explores the rich research literature in detail. Each chapter concludes with a section devoted to notes and bibliographical remarks and all abstract results are illustrated by examples. The tools used include many classical and modern nonlinear analysis methods such as fixed-point theorems, as well as some notions of Ulam stability, attractivity and the measure of non-compactness as well as the measure of weak noncompactness. It is useful for researchers and graduate students for research, seminars, and advanced graduate courses, in pure and applied mathematics, physics, mechanics, engineering, biology, and all other applied sciences.

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Book SynopsisTopics covered in Discrete Mathematics have become essential tools in many areas of studies in recent years. This is primarily due to the revolution in technology, communications, and cyber security. The book treats major themes in a typical introductory modern Discrete Mathematics course: Propositional and predicate logic, proof techniques, set theory (including Boolean algebra, functions and relations), introduction to number theory, combinatorics and graph theory.An accessible, precise, and comprehensive approach is adopted in the treatment of each topic. The ability of abstract thinking and the art of writing valid arguments are emphasized through detailed proof of (almost) every result. Developing the ability to think abstractly and roguishly is key in any areas of science, information technology and engineering. Every result presented in the book is followed by examples and applications to consolidate its comprehension. The hope is that the reader ends up developing both the abstract reasoning as well as acquiring practical skills.All efforts are made to write the book at a level accessible to first-year students and to present each topic in a way that facilitates self-directed learning. Each chapter starts with basic concepts of the subject at hand and progresses gradually to cover more ground on the subject. Chapters are divided into sections and subsections to facilitate readings. Each section ends with its own carefully chosen set of practice exercises to reenforce comprehension and to challenge and stimulate readers.As an introduction to Discrete Mathematics, the book is written with the smallest set of prerequisites possible. Familiarity with basic mathematical concepts (usually acquired in high school) is sufficient for most chapters. However, some mathematical maturity comes in handy to grasp some harder concepts presented in the book.

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Book SynopsisOne of the central highlights of this work is the exploration of the Yoneda lemma and its profound implications, during which intuitive explanations are provided, as well as detailed proofs, and specific examples. This book covers aspects of category theory often considered advanced in a clear and intuitive way, with rigorous mathematical proofs. It investigates universal properties, coherence, the relationship between categories and graphs, and treats monads and comonads on an equal footing, providing theorems, interpretations and concrete examples. Finally, this text contains an introduction to monoidal categories and to strong and commutative monads, which are essential tools in current research but seldom found in other textbooks.Starting Category Theory serves as an accessible and comprehensive introduction to the fundamental concepts of category theory. Originally crafted as lecture notes for an undergraduate course, it has been developed to be equally well-suited for individuals pursuing self-study. Most crucially, it deliberately caters to those who are new to category theory, not requiring readers to have a background in pure mathematics, but only a basic understanding of linear algebra.

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Book SynopsisThis research monograph explores new frontiers in Markov chains. Although time-homogeneous Markov chains are well understood, this is not at all the case with time-inhomogeneous ones. The book, after a review on the classical theory of homogeneous chains, including the electrical network approach, introduces several new models which involve inhomogeneous chains as well as related new types of random walks (for example, 'coin turning', 'conservative' and 'Rademacher' walk). Scaling limits, the breakdown of the classical limit theorems as well as recurrence and transience are investigated. The relationship with urn models is the subject of two chapters, providing additional connections to other parts of probability theory.Random walks on random graphs are discussed as well, as an area where the method of electric networks is especially useful. This is illustrated by presenting random walks in random environments and random labyrinths.The monograph puts emphasis on showing examples and open problems besides providing rigorous analysis of the models.Several figures illustrate the main ideas, and a large number of exercises challenge the interested reader.

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Book SynopsisThis book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.Trade Review“This monograph ... is intended to be a textbook for graduate students in statistics, computer science and engineering. It covers a very broad range of topics ... . Each chapter is finished by a rather long list of relevant references. Thus, it can be used also as a reference book by researches in the fields of machine learning, pattern recognition ... . it can be a useful reference to many important Monte Carol methods.” (Jaromír Antoch, zbMATH 1483.65001, 2022)“True to its goal, the text offers a comprehensive overview on Monte Carlo methods. … this text is a quality reference for researchers interested in computer vision, computer graphics, machine learning, artificial intelligence and related fields.” (Grant Innerst, MAA Reviews, July 18, 2021)Table of Contents1 Introduction to Monte Carlo Methods.- 2 Sequential Monte Carlo.- 3 Markov Chain Monte Carlo - the Basics.- 4 Metropolis Methods and Variants.- 5 Gibbs Sampler and its Variants.- 6 Cluster Sampling Methods.- 7 Convergence Analysis of MCMC.- 8 Data Driven Markov Chain Monte Carlo.- 9 Hamiltonian and Langevin Monte Carlo.- 10 Learning with Stochastic Gradient.- 11 Mapping the Energy Landscape.

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Book SynopsisThis book explains the notion of Brakke’s mean curvature flow and its existence and regularity theories without assuming familiarity with geometric measure theory. The focus of study is a time-parameterized family of k-dimensional surfaces in the n-dimensional Euclidean space (1 ≤ k < n). The family is the mean curvature flow if the velocity of motion of surfaces is given by the mean curvature at each point and time. It is one of the simplest and most important geometric evolution problems with a strong connection to minimal surface theory. In fact, equilibrium of mean curvature flow corresponds precisely to minimal surface. Brakke’s mean curvature flow was first introduced in 1978 as a mathematical model describing the motion of grain boundaries in an annealing pure metal. The grain boundaries move by the mean curvature flow while retaining singularities such as triple junction points. By using a notion of generalized surface called a varifold from geometric measure theory which allows the presence of singularities, Brakke successfully gave it a definition and presented its existence and regularity theories. Recently, the author provided a complete proof of Brakke’s existence and regularity theorems, which form the content of the latter half of the book. The regularity theorem is also a natural generalization of Allard’s regularity theorem, which is a fundamental regularity result for minimal surfaces and for surfaces with bounded mean curvature. By carefully presenting a minimal amount of mathematical tools, often only with intuitive explanation, this book serves as a good starting point for the study of this fascinating object as well as a comprehensive introduction to other important notions from geometric measure theory.

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Book SynopsisThis book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.Table of ContentsPreface Acknowledgements 1 Introduction to Sample Size Determination Introduction Issue of Power due to inappropriate sample size Some case studies Flow Diagram of Determining sample size and power Summary 2 Understanding Statistical Inference Introduction Estimating Parameters Estimating Population Mean Confidence Coefficient Confidence Interval Factors Affecting Confidence Interval Estimating Population Proportion Hypothesis Testing Type I and Type II Errors Power of the Test Relationship between Type I and Type II Errors One Tailed and Two Tailed Tests Procedure in Hypothesis Testing Experiment Effect Size Summary 3 Understanding Concepts in Estimating Sample Size in Survey Studies Introduction Determining Sample Size in Estimating Population Mean Factors Affecting Sample Size Sample Size Determination for Estimating Mean when Population SD Known: Illustration 3.1 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.2 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.3 Sample Size Determination for Estimating Mean when Population SD Unknown: Illustration 3.4 Determining Sample Size in Estimating Population Proportion Sample Size Determination for Estimating Proportion: Illustration 3.5 Sample Size Determination for Estimating Proportion: Illustration 3.6 Sample Size Determination for Estimating Proportion: Illustration 3.7 Sample Size Determination for Estimating Proportion: Illustration 3.8 Determining Sample Size in Estimating Difference Between Two Population Means Summary 4 Understanding Concepts in Estimating Sample Size in Hypothesis Testing Experiment Introduction Sample Size on the Basis of Power One Sample Testing of Mean Determining Sample Size Estimation of Minimum Sample Size to Test H0 : µ=37 : Illustration 4.1 Minimum Detectable Difference Estimation of Minimum Detectable Difference for Testing H0: µ=37: Illustration 4.2 Estimation of Power in One Sample t Test Estimation of Power in Testing H0: µ=37: Illustration 4.3 Testing Difference Between Two Means Determining Sample Size in Two Sample t Test Estimation of Sample Size for Two Sample t Test for Mean : Illustration 4.4 Estimation of Power in Two Sample t Test Estimation of Power in Two Sample t Test for Mean : Illustration 4.5 Summary 5 Use of G*Power Software Introduction Procedure of Installing G*Power 3.1 Summary 6 Determining Sample Size in Experimental Studies Introduction One Sample Testing Testing Difference of Sample Mean from Population Mean Sample Size and Power Determination: Illustration 6.1 Testing Difference of Sample Proportion from Population Proportion Sample Size Determination: Illustration 6.2 Two Sample Testing Comparing Group Means in Two Independent Samples Sample Size and Power Determination: Illustration 6.3 Comparing Paired Group Means Sample Size Determination: Illustration 6.4 Comparing two Group Means Using Mann Whitney Test Sample Size Determination: Illustration 6.5 Comparing Paired Group Means Using Wilcoxon Signed Rank Test Sample Size Determination: Illustration 6.6 Comparing Two Proportions Sample Size Determination: Illustration 6.7 Correlation Coefficient: Testing Significance Case I: Testing Whether Sample Correlation Differs From 0 Sample Size Determination: Illustration 6.14 Case II: Testing Whether Sample Correlation Differs from a Known Value Sample Size Determination: Illustration 6.15 Correlation Coefficients: Testing Significant Difference Between Two Independent Correlations Sample Size Determination: Illustration 6.16 Bi-Serial Correlation: Testing Significance Sample Size Determination: Illustration 6.17 Goodness of Fit: Testing With Chi-Square Sample Size Determination in Goodness of Fit: Illustration 6.18 Linear Multiple Regression Model Sample Size Determination in Linear Multiple Regression: Illustration 6.19 Logistic Regression Sample Size Determination for Continuous Predictors: Illustration 6.20 Sample Size Determination for a Dichotomous Predictor: Illustration 6.21 Summary 7 Determining Sample Size in General Linear Models Introduction Analysis of Variance One–Way Analysis of Variance Sample Size Determination: Illustration 6.8 Two–Way Analysis of Variance Sample Size Determination for Main and Interaction Effect: Illustration 6.9 Repeated Measures ANOVA Between Factors Sample Size Determination: Illustration 6.10 Repeated Measures ANOVA Within Factors Sample Size Determination: Illustration 6.11 Repeated ANOVA Within-Between Interaction Manova Experiment: for Testing the Significance of Global Effect Sample Size Determination: Illustration 6.12 Manova Experiment: Testing Significance of Interaction Effect Sample Size Determination: Illustration 6.13 Summary Appendix Bibliography

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Book SynopsisThis book discusses comprehensively the advanced manufacturing processes, including illustrative examples of the processes, mathematical modeling, and the need to optimize associated parameter problems. In addition, it describes in detail the cohort intelligence methodology and its variants along with illustrations, to help readers gain a better understanding of the framework. The theoretical and statistical rigor is validated by comparing the solutions with evolutionary algorithms, simulation annealing, response surface methodology, the firefly algorithm, and experimental work. Lastly, the book critically reviews several socio-inspired optimization methods. Table of ContentsIntroduction.- A Brief Review of Socio-Inspired Metaheuristics.- Multi Cohort Intelligence Algorithm.- Optimization of Electric Discharge Machining (EDM).- Optimization of Abrasive Water Jet Machining (AWJM).- Optimization of Micro Milling Process.- Optimization of Micro Drilling Process.- Optimization of Cutting Forces in Micro Drilling of CFRP Composites for Aerospace Applications.- Optimization of Micro Turning Process.- Optimization of Machining Process Parameters of Titanium Alloy Under (MQL) Environment.

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Book SynopsisThis book aims to establish a foundation for fractional derivatives and fractional differential equations. The theory of fractional derivatives enables considering any positive order of differentiation. The history of research in this field is very long, with its origins dating back to Leibniz. Since then, many great mathematicians, such as Abel, have made contributions that cover not only theoretical aspects but also physical applications of fractional calculus. The fractional partial differential equations govern phenomena depending both on spatial and time variables and require more subtle treatments. Moreover, fractional partial differential equations are highly demanded model equations for solving real-world problems such as the anomalous diffusion in heterogeneous media. The studies of fractional partial differential equations have continued to expand explosively. However we observe that available mathematical theory for fractional partial differential equations is not still complete. In particular, operator-theoretical approaches are indispensable for some generalized categories of solutions such as weak solutions, but feasible operator-theoretic foundations for wide applications are not available in monographs.To make this monograph more readable, we are restricting it to a few fundamental types of time-fractional partial differential equations, forgoing many other important and exciting topics such as stability for nonlinear problems. However, we believe that this book works well as an introduction to mathematical research in such vast fields.Trade Review“The book is written nicely and useful as an introductory book on time fractional derivatives in abstract spaces.” (Syed Abbas, zbMATH 1485.34002, 2022)Table of Contents

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Book SynopsisThe Yau-Tian-Donaldson conjecture for anti-canonical polarization was recently solved affirmatively by Chen-Donaldson-Sun and Tian. However, this conjecture is still open for general polarizations or more generally in extremal Kähler cases. In this book, the unsolved cases of the conjecture will be discussed.It will be shown that the problem is closely related to the geometry of moduli spaces of test configurations for polarized algebraic manifolds. Another important tool in our approach is the Chow norm introduced by Zhang. This is closely related to Ding’s functional, and plays a crucial role in our differential geometric study of stability. By discussing the Chow norm from various points of view, we shall make a systematic study of the existence problem of extremal Kähler metrics.Trade Review“The concise style of exposition likely means that this monograph is best suited for experts with background knowledge in canonical Kähler metrics. … It can be recommended also to those who would like a review of important results concerning the generalised Kähler-Einstein metrics, with various examples, and the moduli space of Lp-spaces.” (Yoshinori Hashimoto, Mathematical Reviews, May, 2023)Table of ContentsIntroduction.- The Donaldson-Futaki invariant.- Canonical Kähler metrics.- Norms for test configurations.- Stabilities for polarized algebraic manifolds.- The Yau-Tian-Donaldson conjecture.- Stability theorem.- Existence problem.- Canonical Kähler metrics on Fano manifolds.- Geometry of pseudo-normed graded algebras.- Solutions.

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Book SynopsisThis book explores recent developments in theoretical research and mathematical modelling of real-world complex systems, organized in four parts. The first part of the book is devoted to the mathematical tools for the design and analysis in engineering and social science study cases. We discuss the periodic evolutions in nonlinear chemical processes, vibro-compact systems and their behaviour, different types of metal–semiconductor self-assembled samples, made of silver nanowires and zinc oxide nanorods. The second part of the book is devoted to mathematical description and modelling of the critical events, climate change and robust emergency scales. In three chapters, we consider a climate-economy model with endogenous carbon intensity and the behaviour of Tehran Stock Exchange market under international sanctions. The third part of the book is devoted to fractional dynamic and fractional control problems. We discuss the novel operational matrix technique for variable-order fractional optimal control problems, the nonlinear variable-order time fractional convection–diffusion equation with generalized polynomials The fourth part of the book concerns solvability and inverse problems in differential and integro-differential equations. The book facilitates a better understanding of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical theory to apply nonlinear design to practical engineering. It can be read by mathematicians, physicists, complex systems scientists, IT specialists, civil engineers, data scientists and urban planners.Table of ContentsAlbert C.J. Luo, The Chinese Calligraphy in Memory of Professor Valentin Afraimovich (1945-2018) Chapter 01: Mayra Angélica Bárcenas-Castro, Ramón Díaz de León-Zapata, Saúl Almazán-Cuéllar, Efrén Flores-García, Gustavo Vera-Reveles, José Vulfrano González-Fernández, Applications of the fundamentals of Bézier curves Chapter 02: Siyu Guo, Albert C. J. Luo On complex periodic evolutions of a periodically diffused Brussellator Chapter 03: Victor Bazhenov, Olga Pogorelova, Tatiana Postnikova Analysis of Intermittent and Quasi-periodic Transitions to Chaos in Vibro-impact System with Continuous Wavelet Transform Chapter 04: Lev A. Ostrovsky, Yury A. Stepanyants Complex Dynamics of Solitons in Rotating Fluids Chapter 05: Dmitry V. Kovalevsky A Climate-Economy Model with Endogenous Carbon Intensity Chapter 06: Abootaleb Shirvani, Dimitri Volchenkov A Regulated Market Under Sanctions. On Tail Dependence Between Oil, Gold, and Tehran Stock Exchange Index Chapter 07: Dmitry V. Kovalevsky and Mara Manez Costa Dynamics of Water-Constrained Economies Affected by Climate Change: Nonlinear and Stochastic Effects Chapter 08: H. Hassani, J. A. Tenreiro Machado An efficient operational matrix technique for variable-order fractional optimal control problems Chapter 09: H. Hassani, J. A. Tenreiro Machado, Z. Avazzadeh, E. Naraghirad Solving nonlinear variable-order time fractional convection-diffusion equation with generalized polynomials Chapter 10: C. Connell McCluskey ,Vitali Vougalter Inverse problems for some systems of parabolic equations Chapter 11: Vitali Vougalter, Vitaly Volpert Solvability In The Sense Of Sequences For Some Non Fredholm Operators With The Bi-Laplacian

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Book SynopsisThis third of the three-volume book is targeted as a basic course in algebraic topology and topology for fiber bundles for undergraduate and graduate students of mathematics. It focuses on many variants of topology and its applications in modern analysis, geometry, and algebra. Topics covered in this volume include homotopy theory, homology and cohomology theories, homotopy theory of fiber bundles, Euler characteristic, and the Betti number. It also includes certain classic problems such as the Jordan curve theorem along with the discussions on higher homotopy groups and establishes links between homotopy and homology theories, axiomatic approach to homology and cohomology as inaugurated by Eilenberg and Steenrod. It includes more material than is comfortably covered by beginner students in a one-semester course. Students of advanced courses will also find the book useful. This book will promote the scope, power and active learning of the subject, all the while covering a wide range of theory and applications in a balanced unified way.Table of Contents1. Prerequisite Concepts of Topology, Algebra and Category Theory.- 2. Homotopy Theory: Fundamental and Higher Homotopy Groups.- 3. Homology and Cohomology Theories: An Axiomatic Approach with Consequences.- 4. Topology of Fiber Bundles.- 5. Homotopy Theory of Bundles.- 6. Some Applications of Algebraic Topology.- 7. Brief History on Algebraic Topology and Fiber Bundles.

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Book SynopsisThis book is an exposition of recent progress on the Donaldson–Thomas (DT) theory. The DT invariant was introduced by R. Thomas in 1998 as a virtual counting of stable coherent sheaves on Calabi–Yau 3-folds. Later, it turned out that the DT invariants have many interesting properties and appear in several contexts such as the Gromov–Witten/Donaldson–Thomas conjecture on curve-counting theories, wall-crossing in derived categories with respect to Bridgeland stability conditions, BPS state counting in string theory, and others. Recently, a deeper structure of the moduli spaces of coherent sheaves on Calabi–Yau 3-folds was found through derived algebraic geometry. These moduli spaces admit shifted symplectic structures and the associated d-critical structures, which lead to refined versions of DT invariants such as cohomological DT invariants. The idea of cohomological DT invariants led to a mathematical definition of the Gopakumar–Vafa invariant, which was first proposed by Gopakumar–Vafa in 1998, but its precise mathematical definition has not been available until recently.This book surveys the recent progress on DT invariants and related topics, with a focus on applications to curve-counting theories.Trade Review“The book is directed at readers with a solid foundation in algebraic geometry. … the main definitions and theorems are nicely illustrated by examples. … The book will serve as a guide to further reading for those wishing to learn more details about the theory.” (Matthew B. Young, Mathematical Reviews, March, 2023)Table of Contents1Donaldson–Thomas invariants on Calabi–Yau 3-folds.- 2Generalized Donaldson–Thomas invariants.- 3Donaldson–Thomas invariants for quivers with super-potentials.- 4Donaldson–Thomas invariants for Bridgeland semistable objects.- 5Wall-crossing formulas of Donaldson–Thomas invariants.- 6Cohomological Donaldson–Thomas invariants.- 7Gopakumar–Vafa invariants.- 8Some future directions.

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Book SynopsisThis monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947. Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This new edition is organized in two volumes. The first volume addresses foundations of LP, including the geometry of feasible region, the simplex method and its implementation, duality and the dual simplex method, the primal-dual simplex method, sensitivity analysis and parametric LP, the generalized simplex method, the decomposition method, the interior-point method and integer LP method. The second volume mainly introduces contributions of the author himself, such as efficient primal/dual pivot rules, primal/dual Phase-I methods, reduced/D-reduced simplex methods, the generalized reduced simplex method, primal/dual deficient-basis methods, primal/dual face methods, a new decomposition principle, etc.Many important improvements were made in this edition. The first volume includes new results, such as the mixed two-phase simplex algorithm, dual elimination, fresh pricing scheme for reduced cost, bilevel LP models and intercepting of optimal solution set. In particular, the chapter Integer LP Method was rewritten with great gains of the objective cutting for new ILP solvers {\it controlled-cutting/branch} methods, as well as with an attractive implementation of the controlled-branch method. In the second volume, the `simplex feasible-point algorithm' was rewritten, and removed from the chapter Pivotal Interior-Point Method to form an independent chapter with the new title `Simplex Interior-Point Method', as it represents a class of efficient interior-point algorithms transformed from traditional simplex algorithms. The title of the original chapter was then changed to `Facial Interior-Point Method', as the remaining algorithms represent another class of efficient interior-point algorithms transformed from normal interior-point algorithms. Without exploiting sparsity, the original primal/dual face methods were implemented using Cholesky factorization. In order to deal with sparse computation, two new chapters discussing LU factorization were added to the second volume. The most exciting improvement came from the rediscovery of the reduced simplex method. In the first edition, the derivation of its prototype was presented in a chapter with the same title, and then converted into the so-called `improved' version in another chapter. Fortunately, the author recently found a quite concise new derivation, so he can now introduce the distinctive fresh simplex method in a single chapter. It is exciting that the reduced simplex method can be expected to be the best LP solver ever.With a focus on computation, the current edition contains many novel ideas, theories and methods, supported by solid numerical results. Being clear and succinct, its content reveals in a fresh manner, from simple to profound. In particular, a larger number of examples were worked out to demonstrate algorithms. This book is a rare work in LP and an indispensable tool for undergraduate and graduate students, teachers, practitioners, and researchers in LP and related fields.Table of ContentsChapter 1. Introduction.- Chapter 2. Geometry of Feasible Region.- Chapter 3. Simplex Method.- Chapter 4. Implementation of Simplex Method.- Chapter 5. Duality Principle and Dual Simplex Method.- Chapter 6. Primal-Dual Simplex Method.- Chapter 7. Sensitivity Analysis and Parametric LP.- Chapter 8. Generalized Simplex Method.- Chapter 9. Decomposition Method.- Chapter 10. Interior-Point Method.- Chapter 11. Integer Linear Programming (ILP).- Chapter 12. Pivot Rule.- Chapter 13. Dual Pivot Rule.- Chapter 14. Simplex Phase-I Method.- Chapter 15. Dual Simplex Phase-l Method.- Chapter 16. Reduced Simplex Method.- Chapter 17. D-Reduced Simplex Method.- Chapter 18. Generalized Reduced Simplex Method.- Chapter 19. Deficient-Basis Method.- Chapter 20. Dual Decient-Basis Method.- Chapter 21. Face Method with Cholesky Factorization.- Chapter 22. Dual Face Method with Cholesky Factorization.- Chapter 23. Face Method with LU Factorization.- Chapter 24. Dual Face Method with LU Factorization.- Chapter 25. Simplex Interior-Point Method.- Chapter 26. Facial Interior-Point Method.- Chapter 27. Decomposition Principle.

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Book SynopsisThe book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security. A stand-out feature of the book is the availability of reference software code and datasets to replicate the experiments described in the book.Table of ContentsChapter 1: Introduction.- Chapter 2: Fundamental Concepts of Machine Learning.- Chapter 3: Supervised Machine Learning Algorithms for PUF Modeling Attacks.- Chapter 4: Deep Learning based PUF Modeling Attacks.- Chapter 5: Tensor Regression based PUF Modeling Attack.- Chapter 6: Binarized Neural Network based PUF Modeling.- Chapter 7: Conclusions and Future Work.

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Book SynopsisThis open access book is intended for common readers who are interested in the life story of Qian Xuesen (also know as Tsien Hsue-Shen). Based on a large number of original archives and historical materials, this book focuses on Qian Xuesen’s years of seeking knowledge from his birth in 1911 to his return to China in 1955 and describes how he grows into a world-known scientist from the aspect of humanity. This book can be used as reference material for Qian Xuesen’s earlier years.Table of ContentsChapter 1 Family and Education.- Chapter 2 Serve the Country through Engineering.- Chapter 3 Life and Study in the United States.- Chapter 4 From Young Scholar to World-Class Scientist.- Chapter 5 Marriage and Family Life.- Chapter 6 Communism Enlightenment and Dedication to His Country.

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Book SynopsisThis book exposes the internal structure of non-self-adjoint operators acting on complex separable infinite dimensional Hilbert space, by analyzing and studying the commutant of operators. A unique presentation of the theorem of Cowen-Douglas operators is given. The authors take the strongly irreducible operator as a basic model, and find complete similarity invariants of Cowen-Douglas operators by using K-theory, complex geometry and operator algebra tools.

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Book SynopsisShiing-Shen Chern (1911-2004) was one of the leading differential geometers of the twentieth century. In 1946, he founded the Mathematical Institute of Academia Sinica in Shanghai, which was later moved to Nanking. In 1981, he founded the Mathematical Sciences Research Institute (MSRI) at Berkeley and acted as the director until 1984. In 1985, he founded the Nankai Institute of Mathematics in Tianjin. He was awarded the National Medal of Science in 1975; the Wolf Prize in mathematics in 1984; and the Shaw Prize in mathematical sciences in 2004.Chern's works span all the classic fields of differential geometry: the Chern-Simons theory; the Chern-Weil theory, linking curvature invariants to characteristic classes; Chern classes; and other areas such as projective differential geometry and webs that are mathematically rich but currently have a lower profile. He also published work in integral geometry, value distribution theory of holomorphic functions, and minimal submanifolds.Inspired by Chern and his work, former colleagues, students and friends — themselves highly regarded mathematicians in their own right — come together to honor and celebrate Chern's huge contributions. The volume, organized by Phillip Griffiths of the Institute for Advanced Study (Princeton), contains contributions by Michael Atiyah (University of Edinburgh), C-M Bai (Nankai), Robert Bryant (Duke University), Kung-Ching Chang (Peking University), Jeff Cheeger (New York University), Simon K Donaldson (Imperial College), Hélène Esnault (Universität Duisburg-Essen), Mo-Lin Ge (Nankai), Mark Green (University of California at Los Angeles), Phillip Griffiths (Institute for Advanced Study), F Reese Harvey (Rice University), Alain Hénaut (Université Bordeaux 1), Niky Kamran (McGill University), Bruce Kleiner (Yale), H Blaine Lawson, Jr (Suny at Stony Brook), Yiming Long (Nankai), Xiaonan Ma (UMR 7640 du CNRS), Luc Pirio (IRMAR, France), Graeme Segal (Oxford), Gang Tian (MIT), Jean-Marie Trepreau (Institut de Mathématiques de Jussieu), Jeff Viaclovsky (MIT), Wei Wang (Nankai), Wentsun Wu (Chinese Academy of Sciences), C N Yang (Tsinghua), Tan Zhang (Murray State University), Weiping Zhang (Nankai) and others.Table of ContentsIn Memory of Professor S S Chern (C N Yang); Twisted K-Theory and Cohomology (M Atiyah); Yangian and Its Applications (C-M Bai et al.); Geodesically Reversible Finsler 2-Spheres of Constant Curvature (R L Bryant); Multiple Solutions of the Prescribed Mean Curvature Equation (K C Chang & T Zhang); On the Differentiability of Lipschitz Maps from Metric Measure Spaces to Banach Spaces (J Cheeger & B Kleiner); Two-Forms on Four-Manifolds and Elliptic Equations (S K Donaldson); Partial Connection for p-Torsion Line Bundles in Characteristic p > 0 (H Esnault); Algebraic Cycles and Singularities of Normal Functions, II (M Green & P Griffiths); Planar Web Geometry Through Abelian Relations and Singularities (A Henaut); Transitive Analytic Lie Pseudo-Groups (N Kamran); Stability of Closed Characteristics on Compact Convex Hypersurfaces (Y Long & W Wang); -Invariant and Flat Vector Bundles II (X Ma & W Zhang); On Planar Webs with Infinitesimal Automorphisms (D Marin et al.); Projective Linking and Boundaries of Positive Holomorphic Chains in Projective Manifolds, Part II (F R Harvey & H B Lawson, Jr); Aspects of Metric Geometry of Four Manifolds (G Tian); Algebrisation Des Tissus De Codimension 1: La Generalisation D'un Theoreme De Bol (J-M Trepreau); Conformal Geometry and Fully Nonlinear Equations (J Viaclovsky); Memory of My First Research Teacher: The Great Geometer Chern Shiing-Shen (W Wu); Some Open Gromov-Witten Invariants of the Resolved Conifold (J Zhou).

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Book SynopsisIn China, lots of excellent students who are good at maths take an active part in various maths contests and the best six senior high school students will be selected to form the IMO National Team to compete in the International Mathematical Olympiad. In the past ten years China's IMO Team has achieved outstanding results — they have won the first place almost every year.The author is one of the senior coaches of China's IMO National Team, whose students have won many gold medals many times in IMO.This book is part of the Mathematical Olympiad Series which discusses several aspects related to maths contests, such as algebra, number theory, combinatorics, graph theory and geometry. This book will, in an interesting problem-solving way, explain what probability theory is: its concepts, methods and meanings; particularly, two important concepts — probability and mathematical expectation (briefly expectation) — are emphasized. It consists of 65 problems, appended by 107 exercises and their answers.

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Book SynopsisThis book is devoted to norm estimates for operator-valued functions of one and two operator arguments, as well as to their applications to spectrum perturbations of operators and to linear operator equations, i.e. to equations whose solutions are linear operators. Linear operator equations arise in both mathematical theory and engineering practice. The norm estimates suggested in the book have applications to the theories of ordinary differential, difference, functional-differential and integro-differential equations, as well as to the theories of integral operators and analytic functions. This book provides new tools for specialists in matrix theory and functional analysis. A significant part of the book covers the theory of triangular representations of operators that was developed by L de Branges, M S Brodskii, I C Gohberg, M G Krein, M S Livsic and other mathematicians.

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Book SynopsisThis Finite Element Method offers a fundamental and practical introduction to the finite element method, its variants, and their applications in engineering. Every concept is introduced in the simplest possible setting, while maintaining a level of treatment that is as rigorous as possible without being unnecessarily abstract. Various finite elements in one, two, and three space dimensions are introduced, and their applications to elliptic, parabolic, hyperbolic, and nonlinear equations and to solid mechanics, fluid mechanics, and porous media flow problems are addressed. The variants include the control volume, multipoint flux approximation, nonconforming, mixed, discontinuous, characteristic, adaptive, and multiscale finite element methods. Illustrative computer programs in Fortran and C++ are described. An extensive set of exercises are provided in each chapter. This book serves as a text a for one-semester course for upper-level undergraduates and beginning graduate students and as a professional reference for engineers, mathematicians, and scientists.Table of ContentsOne-Dimensional Model Problems; Two-Dimensional Model Problems; General Variational Formulation; One-Dimensional Elements and Their Properties; Two-Dimensional Elements and Their Properties; Three-Dimensional Elements and Their Properties; Finite Elements for Transient and Nonlinear Problems; Application to Solid Mechanics; Application to Fluid Mechanics; Application to Porous Media Flow; Other Finite Element Methods.

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Book SynopsisThis monograph provides a comprehensive overview on a class of nonlinear evolution equations, such as nonlinear Schrödinger equations, nonlinear Klein-Gordon equations, KdV equations as well as Navier-Stokes equations and Boltzmann equations. The global wellposedness to the Cauchy problem for those equations is systematically studied by using the harmonic analysis methods.This book is self-contained and may also be used as an advanced textbook by graduate students in analysis and PDE subjects and even ambitious undergraduate students.Table of ContentsFourier Multiplier, Function Spaces; Navier-Stokes Equation; Strichartz Estimates for Linear Dispersive Equations; Local and Global Wellposedness for Nonlinear Dispersive Equations; The Low Regularity Theory for the Nonlinear Dispersive Equations; Frequency-Uniform Decomposition Method; Conservations, Morawetz' Inequalities of NLS; Boltzmann Equation without Angular Cutoff.

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Book SynopsisThe book is intended for graduate students of theoretical physics (with a background in quantum mechanics) as well as researchers interested in applications of Lie group theory and Lie algebras in physics. The emphasis is on the inter-relations of representation theories of Lie groups and the corresponding Lie algebras.

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Book SynopsisThis unique book provides a new and well-motivated introduction to calculus and analysis, historically significant fundamental areas of mathematics that are widely used in many disciplines. It begins with familiar elementary high school geometry and algebra, and develops important concepts such as tangents and derivatives without using any advanced tools based on limits and infinite processes that dominate the traditional introductions to the subject. This simple algebraic method is a modern version of an idea that goes back to René Descartes and that has been largely forgotten. Moving beyond algebra, the need for new analytic concepts based on completeness, continuity, and limits becomes clearly visible to the reader while investigating exponential functions.The author carefully develops the necessary foundations while minimizing the use of technical language. He expertly guides the reader to deep fundamental analysis results, including completeness, key differential equations, definite integrals, Taylor series for standard functions, and the Euler identity. This pioneering book takes the sophisticated reader from simple familiar algebra to the heart of analysis. Furthermore, it should be of interest as a source of new ideas and as supplementary reading for high school teachers, and for students and instructors of calculus and analysis.Table of ContentsTangents and Double Points; Derivatives by Algebra; Exponential Functions; Completeness of Real Numbers; The Base of the Natural Exponential and Logarithm Functions; Continuity of Functions; Differentiability; Chain Rule and Other Rules for Derivatives; Derivatives of Trigonometric Functions; Mean Value Inequality and Theorem; Basic Differential Equations; Motion with Constant Acceleration; Linear and Higher Order Approximations; The Antiderivative Problem; Definite Integrals; Fundamental Theorem of Calculus; Integrability of Monotonic Functions; Integrability of Functions with Bounded Derivative; Substitution; Integration by Parts; Taylor's Theorem; Analytic Functions; The Euler Identity;

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a huge range and FREE tracked UK delivery on ALL orders.

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Book Synopsis1. Calculus on Rn.- 2. Manifold Theory.- 3. Differential Forms.- 4. Lie Group.

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Book SynopsisSince antiquity, opposed concepts such a s t he One and the Many, the Finite and the Infinite, and the Absolute and the Relative, have been a driving force in philosophical, scientific, and mathematical thought. Yet they have also given rise to perplexing problems and conceptual paradoxes which continue to haunt scientists and philosophers. In Oppositions and Paradoxes, John L. Bell explains and investigates the paradoxes and puzzles that arise out of conceptual oppositions in physics and mathematics. In the process, Bell not only motivates abstract conceptual thinking about the paradoxes at issue, he also offers a compelling introduction to central ideas in such otherwise-di¬ cult topics as non-Euclidean geometry, relativity, and quantum physics.These paradoxes are often as fun as they are flabbergasting. Consider, for example, the Tristram Shandy paradox: an immortal man composing an autobiography so slowly as to require a year of writing to describe each day of his life—he would, if he had infinite time, never complete the work, although no individual part of it would remain unwritten … Or imagine an English professor who time-travels back to 1599 to offer a printing of Hamlet to William Shakespeare, so as to help the Bard overcome writer’s block and author the play which will centuries later inspire an English professor to travel back in time … These and many other of the book’s paradoxes straddle the boundary between physics and metaphysics, and demonstrate the hidden difficulty of many of our most basic concepts.Trade Review“Who else but John Bell could write a book like this one? One of the leading logicians of our day, Bell uses the role of conceptual oppositions and the paradoxes to which they occasionally give rise to take readers on a whirlwind tour through great swaths of the history of human thought. The sophisticated discussion of deep and difficult topics is highly digestible thanks to Bell wearing his expertise lightly and presenting things with dollops of his clever—and sometimes silly—humour.” — David DeVidi, University of Waterloo“Bell is a master of simplicity and clarity, while sacrificing nothing of accuracy and erudition. His enthusiasm for his subject is palpable and infectious. Oppositions and Paradoxes is a pleasure to read.” — Graham Priest, CUNY Graduate Center“John L. Bell is the true philosophical heir of Bertrand Russell, and his new book, Oppositions and Paradoxes, exemplifies all the best traits in Russell’s legacy. His presentation of philosophical paradoxes and perplexities in logic, mathematics, and physics is a model of lucidity and economy, and his analysis of these problems is secure and sane. Oppositions and Paradoxes is readily accessible and a sure path into some of philosophy’s greatest themes.” — Bradley Bassler, University of GeorgiaTable of ContentsAcknowledgementsWhat Is This Book About?Chapter I: The Continuous and the DiscreteContinuity and DiscretenessThe Pythagorean School and Incommensurable MagnitudesAtomismThe Stoics and the Continuum Theory of MatterZeno’s ParadoxesContemporary Versions of Zeno’s Paradoxes: SupertasksInfinitesimalsChapter II: Oppositions and Paradoxes in Mathematics: Set Theory and the InfiniteSet Theory and the One/Many OppositionParadoxes of the InfiniteUncountable InfinitiesSet-Theoretic AntinomiesThe Axiom of ChoiceChapter III: The Strange Universe of Non-Euclidean GeometryHyperbolic GeometryRiemannian GeometryChapter IV: Puzzles and Paradoxes of Time TravelTime Travel into the Past: Branching TimelinesTemporal LoopsTime Travel into the FutureThe Future Time ViewerTwo-Dimensional TimeTemporal InterdictsTime Travel as a Physical PossibilityChapter V: Puzzles and Paradoxes of Relativity TheorySpecial RelativitySpacetimeFaster-than-Light Particles in Special Relativity: TachyonsGeneral Relativity: The Principle of EquivalenceBlack HolesChapter VI: Puzzles and Paradoxes in Quantum PhysicsWaves vs. ParticlesHeisenberg’s Uncertainty Principle and Bohr’s Principle of ComplementarityQuantum TunnelingThe Riddle of PolarizationSchrödinger’s Cat ParadoxInterpretations of Quantum TheoryThe EPR Paradox and NonlocalityChapter VII: Cosmic EnigmasThe Beginnings of CosmologySteady-State vs. Big BangThe Problem of the Origin of the UniverseDark Matter, Dark Energy, and Cosmic AccelerationThe Argument from Design vs. the MultiverseA Philosophical CodaAppendix 1: Paradoxes in Logic and LanguageThe Liar ParadoxThe Liar, the Truth-Teller, and the Dice ManCurry’s ParadoxThe Grelling-Nelson ParadoxBerry’s ParadoxRichard’s ParadoxThe Paradox of the HeapAppendix 2: Reflections on the Constant and the ChangingAppendix 3: Oppositions in Kant’s PhilosophyAppendix 4: The Principle of Microstraightness, Nilpotent Infinitesimals, and the Differential CalculusFurther ReadingList of OppositionsList of ParadoxesIndex

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Book SynopsisThis book presents the Determinant theory with the use of hypercomplex Grassmann figures. It simplifies the proof of many determinant features. It also states several ways of solutions of linear algebraic systems, most of which are connected with the Determinant theory. The teaching experience in technical universities has demonstrated that the suggested way of presenting the Determinant theory is understood more easily. The title of the book is explained by a desire to attract readers' attention to the well-known in the algebra sphere while introducing a new and more convenient way to present the Determinant theory for technical universities.

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Book SynopsisThis book discusses the importance of knowledge as an intangible asset, separate from physical entities, that can enable us to understand and/or change the world. It provides a thorough treatment of knowledge, one that is free of ideological and philosophical preconceptions, and which relies exclusively on concepts and principles from the theory of computing and logic. It starts with an introduction to knowledge as truthful and useful information, and its development and management by computers and humans. It analyses the relationship between computational processes and physical phenomena, as well as the processes of knowledge production and application by humans and computers. In turn, the book presents autonomous systems that are called upon to replace humans in complex operations as a step toward strong AI, and discusses the risks – real or hypothetical – of the careless use of these systems. It compares human and machine intelligence, attempting to answer the question of whether and to what extent computers, as they stand today, can approach human-level situation awareness and decision-making. Lastly, the book explains the functioning of individual consciousness as an autonomous system that manages short- and long-term objectives on the basis of value criteria and accumulated knowledge. It discusses how individual values are shaped in society and the role of institutions in fostering and maintaining a common set of values for strengthening social cohesion. The book differs from books on the philosophy of science in many respects, e.g. by considering knowledge in its multiple facets and degrees of validity and truthfulness. It follows the dualist tradition of logicians, emphasizing the importance of logic and language and considering an abstract concept of information very different from the one used in the physical sciences. From this perspective, it levels some hopefully well-founded criticism at approaches that consider information and knowledge as nothing more than the emergent properties of physical phenomena. The book strikes a balance between popular books that sidestep fundamental issues and focus on sensationalism, and scientific or philosophical books that are not accessible to non-experts. As such, it is intended for a broad audience interested in the role of knowledge as a driver for change and development, and as a common good whose production and application could shape the future of humanity.Trade Review​In Understanding and Changing the World: From Information to Knowledge and Intelligence, Joseph Sifakis (a 2007 Turing Award recipient) amasses a lifetime of knowledge as a deep thinker and effective practitioner of computer science—indeed, collecting a civilization’s wisdom—to provide a valuable framework that is rooted in the philosophy of science and society."Akash Deshpande, SIAM News, https://sinews.siam.org/Details-Page/intelligence-whence-and-whitherTable of Contents1. Introduction.- Part I For a Gnoseological View of the World.- 2. Fundamental Questions about Knowledge.- 3. Information and Knowledge.- 4. The Development and Application of Knowledge.- Part II Computing, Knowledge and Intelligence.- 5. Physical Phenomena and Computational Processes.- 6. Human vs Artificial Intelligence.- Part III Consciousness and Society.- 7. Consciousness.- 8. Value Systems and Society.- 9. Epilogue.- Index.

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Book SynopsisThis book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.Trade Review“This book is, however, a well-structured and self-contained graduate textbook on ML applications in finance. Exercises and some applications are included at the end of each chapter and the Python code used in this book makes use of the Python Tensor Flow library. This book could also serve as a useful reference book for researchers and practitioners in quantitative finance.” (Gilles Teyssière, Mathematical Reviews, February, 2023)“Each part is introduced with background information, examples of relevant practical applications, and references to the most recent scientific literature. … The book covers all essential areas of machine learning with relevance to quantitative finance. … An additional strong advantage of this book is the clear and consistent structure of its chapters. … Overall, the book covers multiple machine learning approaches with advanced technical exposition and is therefore especially suitable as an academic reference point, especially on Reinforcement Learning.” (Antoniya Shivarova, Financial Markets and Portfolio Management, Issue 35, 2021)“This volume aims to present a broad yet technical treatment of (ML) algorithms used by financial practitioners and scholars alike. … the book fills a large void. … This encourages reproducibility as well as learning by doing, which is highly appreciated.” (Guillaume Coqueret, Quantitative Finance, October 15, 2020)Table of ContentsChapter 1. Introduction.- Chapter 2. Probabilistic Modeling.- Chapter 3. Bayesian Regression & Gaussian Processes.- Chapter 4. Feed Forward Neural Networks.- Chapter 5. Interpretability.- Chapter 6. Sequence Modeling.- Chapter 7. Probabilistic Sequence Modeling.- Chapter 8. Advanced Neural Networks.- Chapter 9. Introduction to Reinforcement learning.- Chapter 10. Applications of Reinforcement Learning.- Chapter 11. Inverse Reinforcement Learning and Imitation Learning.- Chapter 12. Frontiers of Machine Learning and Finance.

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