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Regularity and Complexity in Dynamical Systems
by Albert C. LuoRegularity and Complexity in Dynamical Systems describes periodic and chaotic behaviors in dynamical systems, including continuous, discrete, impulsive, discontinuous, and switching systems. In traditional analysis, the periodic and chaotic behaviors in continuous, nonlinear dynamical systems were extensively discussed even if unsolved. In recent years, there has been an increasing amount of interest in periodic and chaotic behaviors in discontinuous dynamical systems because such dynamical systems are prevalent in engineering. Usually, the smoothening of discontinuous dynamical system is adopted in order to use the theory of continuous dynamical systems. However, such technique cannot provide suitable results in such discontinuous systems. In this book, an alternative way is presented to discuss the periodic and chaotic behaviors in discontinuous dynamical systems.
Regularity and Irregularity of Superprocesses with (1 + β)-stable Branching Mechanism
by Leonid Mytnik Vitali WachtelThis is the only book discussing multifractal properties of densities of stable superprocesses, containing latest achievements while also giving the reader a comprehensive picture of the state of the art in this area. It is a self-contained presentation of regularity properties of stable superprocesses and proofs of main results and can serve as an introductory text for a graduate course. There are many heuristic explanations of technically involved results and proofs and the reader can get a clear intuitive picture behind the results and techniques.
Regularity and Stochasticity of Nonlinear Dynamical Systems
by Dimitri Volchenkov Xavier LeonciniThis book presents recent developments in nonlinear dynamics and physics with an emphasis on complex systems. The contributors provide recent theoretic developments and new techniques to solve nonlinear dynamical systems and help readers understand complexity, stochasticity, and regularity in nonlinear dynamical systems. This book covers integro-differential equation solvability, Poincare recurrences in ergodic systems, orientable horseshoe structure, analytical routes of periodic motions to chaos, grazing on impulsive differential equations, from chaos to order in coupled oscillators, and differential-invariant solutions for automorphic systems, inequality under uncertainty.
Regularity of Difference Equations on Banach Spaces
by Ravi P. Agarwal Claudio Cuevas Carlos LizamaThis work introduces readers to the topic of maximal regularity for difference equations. The authors systematically present the method of maximal regularity, outlining basic linear difference equations along with relevant results. They address recent advances in the field, as well as basic semi group and cosine operator theories in the discrete setting. The authors also identify some open problems that readers may wish to take up for further research. This book is intended for graduate students and researchers in the area of difference equations, particularly those with advance knowledge of and interest in functional analysis.
Regularity Techniques for Elliptic PDEs and the Fractional Laplacian
by Pablo Raúl StingaRegularity Techniques for Elliptic PDEs and the Fractional Laplacian presents important analytic and geometric techniques to prove regularity estimates for solutions to second order elliptic equations, both in divergence and nondivergence form, and to nonlocal equations driven by the fractional Laplacian. The emphasis is placed on ideas and the development of intuition, while at the same time being completely rigorous. The reader should keep in mind that this text is about how analysis can be applied to regularity estimates. Many methods are nonlinear in nature, but the focus is on linear equations without lower order terms, thus avoiding bulky computations. The philosophy underpinning the book is that ideas must be flushed out in the cleanest and simplest ways, showing all the details and always maintaining rigor. Features Self-contained treatment of the topic Bridges the gap between upper undergraduate textbooks and advanced monographs to offer a useful, accessible reference for students and researchers. Replete with useful references.
Regularity Theory for Mean-Field Game Systems
by Diogo A. Gomes Edgard A. Pimentel Vardan VoskanyanBeginning with a concise introduction to the theory of mean-field games (MFGs), this book presents the key elements of the regularity theory for MFGs. It then introduces a series of techniques for well-posedness in the context of mean-field problems, including stationary and time-dependent MFGs, subquadratic and superquadratic MFG formulations, and distinct classes of mean-field couplings. It also explores stationary and time-dependent MFGs through a series of a-priori estimates for solutions of the Hamilton-Jacobi and Fokker-Planck equation. It shows sophisticated a-priori systems derived using a range of analytical techniques, and builds on previous results to explain classical solutions. The final chapter discusses the potential applications, models and natural extensions of MFGs. As MFGs connect common problems in pure mathematics, engineering, economics and data management, this book is a valuable resource for researchers and graduate students in these fields.
The Regularization Cookbook: Explore practical recipes to improve the functionality of your ML models
by Vincent VandenbusscheMethodologies and recipes to regularize any machine learning and deep learning model using cutting-edge technologies such as stable diffusion, Dall-E and GPT-3 Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn to diagnose the need for regularization in any machine learning modelRegularize different ML models using a variety of techniques and methodsEnhance the functionality of your models using state of the art computer vision and NLP techniquesBook DescriptionRegularization is an infallible way to produce accurate results with unseen data, however, applying regularization is challenging as it is available in multiple forms and applying the appropriate technique to every model is a must. The Regularization Cookbook provides you with the appropriate tools and methods to handle any case, with ready-to-use working codes as well as theoretical explanations. After an introduction to regularization and methods to diagnose when to use it, you’ll start implementing regularization techniques on linear models, such as linear and logistic regression, and tree-based models, such as random forest and gradient boosting. You’ll then be introduced to specific regularization methods based on data, high cardinality features, and imbalanced datasets. In the last five chapters, you’ll discover regularization for deep learning models. After reviewing general methods that apply to any type of neural network, you’ll dive into more NLP-specific methods for RNNs and transformers, as well as using BERT or GPT-3. By the end, you’ll explore regularization for computer vision, covering CNN specifics, along with the use of generative models such as stable diffusion and Dall-E. By the end of this book, you’ll be armed with different regularization techniques to apply to your ML and DL models.What you will learnDiagnose overfitting and the need for regularizationRegularize common linear models such as logistic regression Understand regularizing tree-based models such as XGBoosUncover the secrets of structured data to regularize ML modelsExplore general techniques to regularize deep learning modelsDiscover specific regularization techniques for NLP problems using transformers Understand the regularization in computer vision models and CNN architecturesApply cutting-edge computer vision regularization with generative modelsWho this book is forThis book is for data scientists, machine learning engineers, and machine learning enthusiasts, looking to get hands-on knowledge to improve the performances of their models. Basic knowledge of Python is a prerequisite.
The Regularized Fast Hartley Transform
by Keith JonesThe Regularized Fast Hartley Transform provides the reader with the tools necessary to both understand the proposed new formulation and to implement simple design variations that offer clear implementational advantages, both practical and theoretical, over more conventional complex-data solutions to the problem. The highly-parallel formulation described is shown to lead to scalable and device-independent solutions to the latency-constrained version of the problem which are able to optimize the use of the available silicon resources, and thus to maximize the achievable computational density, thereby making the solution a genuine advance in the design and implementation of high-performance parallel FFT algorithms.
Regulation of Sexual Conduct in UN Peacekeeping Operations
by Olivera SimicThis book critically examines the response of the United Nations (UN) to the problem of sexual exploitation in UN Peace Support Operations. It assesses the Secretary-General's Bulletin on Special Protection from Sexual Exploitation and Sexual Abuse (2003) (SGB) and its definition of sexual exploitation, which includes sexual relationships and prostitution. With reference to people affected by the policy (using the example of Bosnian women and UN peacekeepers), and taking account of both radical and 'sex positive' feminist perspectives, the book finds that the inclusion of consensual sexual relationships and prostitution in the definition of sexual exploitation is not tenable. The book argues that the SGB is overprotective, relies on negative gender and imperial stereotypes, and is out of step with international human rights norms and gender equality. It concludes that the SGB must be revised in consultation with those affected by it, namely local women and peacekeepers, and must fully respect their human rights and freedoms, particularly the right to privacy and sexuality rights.
Regulatory Competition in the Digital Economy: Artificial Intelligence, Data, and Platforms (Advanced Studies in Diginomics and Digitalization)
by Michael Denga Lars HornufThe digital economy is reinvigorating regulatory competition, yet little is known about which rules and jurisdictions can effectively bind companies nor what competitive motivations underlie certain rules. In addition to purely economic motives, legislators are now also driving the pursuit of digital sovereignty and the enforcement of social values in digital spaces. It also remains unclear what regulatory weight the self-regulation of private companies has in multi-level governance systems. This book examines regulatory competition in the three main pillars of digital markets: artificial intelligence, data, and platforms. It brings together legal scholars, economists and information systems experts, providing relevant examples and structured analysis of the aims and outcomes of regulatory competition in the digital economy. “A timely exploration of the balancing acts regulators must perform to manage private power in a globalized digital economy. Essential for understanding the intersection of law, economics, and technology in the contemporary digital ecosystem.” Jens Frankenreiter, Associate Professor of Law, Washington University “The book by Denga and Hornuf provides a comprehensive and timely exploration of the intricate regulatory challenges posed by big data, artificial intelligence, and platforms in the Digital Single Market. If offers critical insights for policymakers, scholars, and businesses navigating this evolving landscape.” Philipp Hacker, Professor for Law and Ethics of the Digital Society, European University Viadrin “Artificial Intelligence is fundamentally disrupting how we enable economic growth and how we regulate fair competition. Luckily, Denga and Hornuf provide a detailed and comprehensive overview of the thorniest and most complex regulatory issues while at the same time offering thoughtful and feasible solutions. "Regulatory Competition in the Digital Economy" is a treasure trove for anyone interested in market regulation, fair competition, consumer protection, and geopolitical questions.” Sandra Wachter, Professor of Technology and Regulation, Oxford Internet Institute
Rehabilitation in Practice: Ethnographic Perspectives
by Paul M. W. Hackett Christopher M. Hayre Dave J. MullerThis book focuses on developing the use of ethnographic research for rehabilitation practitioners by recognizing its value methodologically and empirically in the field of rehabilitation. The very nature of ethnographic research offers an array of opportunities for researchers to understand the social world around them. The book identifies the multifaceted use of ethnographic methods in the rehabilitation setting. It touches on how acute and chronic conditions can affect the nature of ethnographic work in attempts to offer originality in a range of rehabilitation settings. Readers will find this collection of examples useful for informing their own research, and it aims to enlighten new discussion and arguments regarding both methodological and empirical use of ethnographic work internationally.
Reimagining Rural Transformation: Market Dynamics and Social Inequalities in North India
by Prashant K TrivediThis book examines the effects of the pattern of growing integration between the rural and urban economies in India. Drawing on in-depth surveys conducted in villages in north India, it examines the rural agricultural economy's transformation, productivity, technology deployment, and social relations over a period of seven years. The book focuses on the socially embedded nature of the dynamics of transformation, weaving analysis around the axis of land, caste, and gender. It also identifies policy gaps and recommends steps for a sustainable and inclusive rural transformation in the Global South.An important contribution to the study of India’s economic and social landscape, this book will be useful for scholars of agriculture, sociology, economics, political science, development studies, and South Asian studies. It will also be of interest to policymakers and journalists interested in rural development, migration, employment, agriculture, and demography.
Reinforcement Learning: Aktuelle Ansätze verstehen – mit Beispielen in Java und Greenfoot
by Uwe LorenzIn uralten Spielen wie Schach oder Go können sich die brillantesten Spieler verbessern, indem sie die von einer Maschine produzierten Strategien studieren. Robotische Systeme üben ihre Bewegungen selbst. In Arcade Games erreichen lernfähige Agenten innerhalb weniger Stunden übermenschliches Niveau. Wie funktionieren diese spektakulären Algorithmen des bestärkenden Lernens? Mit gut verständlichen Erklärungen und übersichtlichen Beispielen in Java und Greenfoot können Sie sich die Prinzipien des bestärkenden Lernens aneignen und in eigenen intelligenten Agenten anwenden. Greenfoot (M.Kölling, King’s College London) und das Hamster-Modell (D.Bohles, Universität Oldenburg) sind einfache, aber auch mächtige didaktische Werkzeuge, die entwickelt wurden, um Grundkonzepte der Programmierung zu vermitteln. Wir werden Figuren wie den Java-Hamster zu lernfähigen Agenten machen, die eigenständig ihre Umgebung erkunden. Die zweite Auflage enthält neue Themen wie "Genetische Algorithmen" und "Künstliche Neugier" sowie Korrekturen und Überarbeitungen.
Reinforcement Learning for Optimal Feedback Control: A Lyapunov-based Approach (Communications and Control Engineering)
by Warren Dixon Joel Rosenfeld Patrick Walters Rushikesh KamalapurkarReinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.
Reinforcement Learning for Reconfigurable Intelligent Surfaces: Assisted Wireless Communication Systems (SpringerBriefs in Computer Science)
by Alice Faisal Ibrahim Al-Nahhal Octavia A. Dobre Telex M. NgatchedThis book presents the intersection of two dynamic fields: Reinforcement Learning (RL) and RIS- Assisted Wireless Communications. With an emphasis on both discrete and continuous problems, it introduces a comprehensive overview of RL techniques and their applications in the evolving world of RIS-assisted wireless communications. Chapter 1 introduces the fundamentals of RL and deep RL (DRL), providing a solid foundation for understanding subsequent chapters. It also presents the Q-learning, deep Q-learning, and deep deterministic policy gradient algorithms. Chapter 2 provides a holistic overview of RIS-assisted systems and details several use cases in wireless communications. Then, Chapters 3 and 4 present various applications of the discrete and continuous DRL to RIS-assisted wireless communications. From maximizing the sum-rate to minimizing, the system resources and maximizing the energy efficiency. These chapters showcase the versatility of the DRL algorithms in tackling arange of challenges. This book concludes with Chapter 5, which introduces the challenges and future directions in this field. It explores the particulars of hyperparameter tuning, problem design, and complexity analysis, while also highlighting the potential of hybrid DRL, multi-agent DRL, and transfer learning techniques for advancing wireless communication systems. Optimizing RIS-Assisted Wireless Systems requires powerful algorithms to cope with the dynamic propagation environment. DRL is envisioned as one of the key enabling techniques to exploit the full potential of RIS-Assisted Wireless Communication Systems. It empowers these systems to intelligently adapt to dynamic wireless environments, maximize performance metrics, and adjusts their configurations to accommodate diverse use cases efficiently. This book serves as a valuable resource, shedding light on the potential of DRL to optimize RIS-Assisted Wireless Communication, enabling researchers, engineers, advanced level students in computer science and electrical engineering and enthusiasts to grasp the intricacies of this topic. It offers a comprehensive understanding of the principles, applications, and challenges, making it a reference to recognize the full potential of the RIS technology in modern wireless communication systems.
Reinforcement Learning in the Ridesharing Marketplace (Synthesis Lectures on Learning, Networks, and Algorithms)
by Hongtu Zhu Jieping Ye Zhiwei (Tony) Qin Xiaocheng Tang Qingyang LiThis book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.
Reinforcement Learning Methods in Speech and Language Technology (Signals and Communication Technology)
by Baihan LinThis book offers a comprehensive guide to reinforcement learning (RL) and bandits methods, specifically tailored for advancements in speech and language technology. Starting with a foundational overview of RL and bandit methods, the book dives into their practical applications across a wide array of speech and language tasks. Readers will gain insights into how these methods shape solutions in automatic speech recognition (ASR), speaker recognition, diarization, spoken and natural language understanding (SLU/NLU), text-to-speech (TTS) synthesis, natural language generation (NLG), and conversational recommendation systems (CRS). Further, the book delves into cutting-edge developments in large language models (LLMs) and discusses the latest strategies in RL, highlighting the emerging fields of multi-agent systems and transfer learning. Emphasizing real-world applications, the book provides clear, step-by-step guidance on employing RL and bandit methods to address challenges in speech and language technology. It includes case studies and practical tips that equip readers to apply these methods to their own projects. As a timely and crucial resource, this book is ideal for speech and language researchers, engineers, students, and practitioners eager to enhance the performance of speech and language systems and to innovate with new interactive learning paradigms from an interface design perspective.
Reinsurance: Actuarial and Statistical Aspects
by Hansjöerg Albrecher Jan Beirlant Jozef L. TeugelsReinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective. The book is written for researchers with an interest in reinsurance problems, for graduate students with a basic knowledge of probability and statistics as well as for reinsurance practitioners. The focus of the book is on modelling together with the statistical challenges that go along with it. The discussed statistical approaches are illustrated alongside six case studies of insurance loss data sets, ranging from MTPL over fire to storm and flood loss data. Some of the presented material also contains new results that have not yet been published in the research literature. An extensive bibliography provides readers with links for further study.
Reinventing Mountain and Rural Villages: Strategies for Regeneration in the Perspective of a Circular Economy (SpringerBriefs in Applied Sciences and Technology)
by Manuela Grecchi Angela Colucci Laura Elisabetta Malighetti Fernanda SpecialeThis book explores problems generated by the abandonment of mountain villages, which also represented strategic sites for guarding against environmental hazards, and proposes a process of regeneration and upgrade of the built environment, with a view to a circular economy and social and economic development. It provides principles, methods, and tools supporting the design and management of the regeneration of abandoned mountain/rural villages and presents the transferable results of multidisciplinary applied research involving several local contexts and compares methodological and technical design solutions developed in successful practices. The book consists of six chapters that address specific issues in the regeneration process of depopulated mountain villages.
Rekenek 101: Pushing Mathematical Understanding
by Amy HowDesigned and developed by a mathematic curriculum researcher at the Freudenthal Institute at Utrecht University, the rekenrek is an exciting and innovative classroom tool that enhances and supports the natural development of number sense in children. It encourages learning across a range of mathematical skills and concepts, from simple addition and subitization to commutativity, distributive property and fractions. However, despite the potential and versatility of this manipulative, there has been surprisingly little written about either its application or its benefits - until now.When the stacks of rekenreks first arrived at Amy How's school, she was tasked with discovering and explaining their function to the rest of the staff - despite the scarcity of current research or other information. Over the six years since, she has developed her own set of tasks and strategies, which she regularly presents to teachers around the world. These techniques – effective, straightforward and very popular – are the basis of this book. Rekenrek 101 is written in a format that makes for a useful teacher resource: not too long; clear, concise and inspiring enough for readers to try the new ideas the next day in class. It is easy to follow and easy to navigate while demonstrating a simple change in practice that stays up with current trends. This is not a book on theory, but it is based on what the latest research is telling us.
Rekenrek 101: Pushing Mathematical Understanding
by Amy HowDesigned and developed by a mathematic curriculum researcher at the Freudenthal Institute at Utrecht University, the rekenrek is an exciting and innovative classroom tool that enhances and supports the natural development of number sense in children. It encourages learning across a range of mathematical skills and concepts, from simple addition and subitization to commutativity, distributive property and fractions. However, despite the potential and versatility of this manipulative, there has been surprisingly little written about either its application or its benefits - until now.When the stacks of rekenreks first arrived at Amy How's school, she was tasked with discovering and explaining their function to the rest of the staff - despite the scarcity of current research or other information. Over the six years since, she has developed her own set of tasks and strategies, which she regularly presents to teachers around the world. These techniques – effective, straightforward and very popular – are the basis of this book. Rekenrek 101 is written in a format that makes for a useful teacher resource: not too long; clear, concise and inspiring enough for readers to try the new ideas the next day in class. It is easy to follow and easy to navigate while demonstrating a simple change in practice that stays up with current trends. This is not a book on theory, but it is based on what the latest research is telling us.
Relational and Algebraic Methods in Computer Science: 17th International Conference, RAMiCS 2018, Groningen, The Netherlands, October 29 – November 1, 2018, Proceedings (Lecture Notes in Computer Science #11194)
by Jules Desharnais Walter Guttmann Stef JoostenThis book constitutes the proceedings of the 17th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2018, held in Groningen, The Netherlands, in October/November 2018. The 21 full papers and 1 invited paper presented together with 2 invited abstracts and 1 abstract of a tutorial were carefully selected from 31 submissions. The papers are organized in the following topics: Theoretical foundations; reasoning about computations and programs; and applications and tools.
Relational and Algebraic Methods in Computer Science: 21st International Conference, RAMiCS 2024, Prague, Czech Republic, August 19–22, 2024, Proceedings (Lecture Notes in Computer Science #14787)
by Uli Fahrenberg Roland Glück Wesley FussnerThis book constitutes the refereed proceedings of the 21st International Conference, RAMiCS 2024, held in Prague, Czech Republic, during August 19–22, 2024. The 15 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on mathematical foundations to applications as conceptual and methodological tools in computer science and beyond.
Relational and Algebraic Methods in Computer Science: 18th International Conference, RAMiCS 2020, Palaiseau, France, October 26–29, 2020, Proceedings (Lecture Notes in Computer Science #12062)
by Uli Fahrenberg Peter Jipsen Michael WinterThis book constitutes the proceedings of the 18th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2020, which was due to be held in Palaiseau, France, in April 2020. The conference was cancelled due to the COVID-19 pandemic. The 20 full papers presented together with 3 invited abstracts were carefully selected from 29 submissions. Topics covered range from mathematical foundations to applications as conceptual and methodological tools in computer science and beyond.
Relational and Algebraic Methods in Computer Science
by Peter Höfner Damien Pous Georg StruthThis volume contains the proceedings of the 7th International Seminar on - lational Methods in Computer Science (RelMiCS 7) and the 2nd International Workshop onApplications ofKleeneAlgebra. Thecommonmeetingtookplacein Bad Malente (near Kiel), Germany, from May May 12-17,2003. Its purpose was to bring together researchers from various subdisciplines of Computer Science, Mathematics and related ?elds who use the calculi of relations and/or Kleene algebra as methodological and conceptual tools in their work. This meeting is the joint continuation of two di'erent series of meetings. Previous RelMiCS seminars were held in Schloss Dagstuhl (Germany) in J- uary 1994, Parati (Brazil) in July 1995, Hammamet (Tunisia) in January 1997, Warsaw (Poland) in September 1998, Quebec (Canada) in January 2000, and Oisterwijk (The Netherlands) in October 2001. The ?rst workshop on appli- tions of Kleene algebra was also held in Schloss Dagstuhl in February 2001. To join these two events in a common meeting was mainly motivated by the s- stantialcommoninterestsandoverlapofthetwocommunities. Wehopethatthis leads to fruitful interactions and opens new and interesting research directions.