Matematisk datateori

This book addresses the urgent issue of massive and inefficient energy consumption by data centers, which have become the largest co-located computing systems in the world and process trillions of megabytes of data every second. Dynamic provisioning algorithms have the potential to be the most viable and convenient of approaches to reducing data center energy consumption by turning off unnecessary servers, but they incur additional costs from being unable to properly predict future workload demands that have only recently been mitigated by advances in machine-learned predictions.This book explores whether it is possible to design effective online dynamic provisioning algorithms that require zero future workload information while still achieving close-to-optimal performance. It also examines whether characterizing the benefits of utilizing the future workload information can then improve the design of online algorithms with predictions in dynamic provisioning. The book specifically develops online dynamic provisioning algorithms with and without the available future workload information. Readers will discover the elegant structure of the online dynamic provisioning problem in a way that reveals the optimal solution through divide-and-conquer tactics. The book teaches readers to exploit this insight by showing the design of two online competitive algorithms with competitive ratios characterized by the normalized size of a look-ahead window in which exact workload prediction is available.

This book constitutes the revised selected papers of the 8th Summer School, CEFP 2019, held in Budapest, Hungary, during June 2019.The 7 full papers and the 4 short papers included in this volume were carefully reviewed and selected. The lectures cover various programming subjects with a focus on composability, comprehensibility, and correctness of working software.

This book provides essential information on Petri net theory and Petri net-based model checking methods. As for the Petri net theory, it involves the interleaving semantics and concurrency semantics of elementary net systems, some important net structures (e.g., invariant, repetitive vector, siphon, and trap), some classical net subclasses with special structures (e.g., state machine, marked graph, free-choice net,asymmetric-choice net, normal net, and weakly persistent net), and some basic properties (e.g., reachability, liveness, deadlock, and soundness). It also involves four high-level Petri nets: knowledge-oriented Petri nets, Petri nets with insecure places, time Petri nets, and plain time Petri nets with priorities, focusing on different fields of application. As for the model checking methods, this book introduces readers to computation tree logic (CTL), computation tree logic of knowledge (CTLK), and timed computation tree logic (TCTL), as well as Petri net-based methods for checking them. The basic principle of the reduced ordered binary decision diagram (ROBDD) is employed to compress the state space used in these model checking procedures. The book also covers time-soundness for time Petri nets and secure bisimulation for Petri nets with insecure places, both of which are based on the bisimulation theory. As such, it offers an introduction to basic information on bisimulation theory.

This book constitutes the refereed proceedings of the 7th International Joint Conference on Rules and Reasoning, RuleML+RR 2023, held in Oslo, Norway, during September 18¿20, 2023. The 13 full papers and 3 short papers included in these proceedings were carefully reviewed and selected from 46 submissions. They focus on all aspects of theoretical advances; novel technologies; innovative applications; knowledge representation; reasoning with rules; and research, development, applications of rule-based systems.

This book presents a set of software engineering techniques and tools to improve the productivity and assure the quality in quantum software development. Through the collaboration of the software engineering community with the quantum computing community new architectural paradigms for quantum-enabled computing systems will be anticipated and developed.The book starts with a chapter that introduces the main concepts and general foundations related to quantum computing. This is followed by a number of chapters dealing with the quantum software engineering methods and techniques. Topics like the Talavera Manifesto for quantum software engineering, frameworks for hybrid systems, formal methods for quantum software engineering, quantum software modelling languages, and reengineering for quantum software are covered in this part. A second set of chapters then deals with quantum software environments and tools, detailing platforms like QuantumPath(R), Classiq as well as quantum software frameworks for deep learning. Overall, the book aims at academic researchers and practitioners involved in the creation of quantum information systems and software platforms. It is assumed that readers have a background in traditional software engineering and information systems.

This book constitutes the proceedings of the 24th International Conference on Formal Methods and Software Engineering, ICFEM 2023, held in Brisbane, QLD, Australia, during November 21¿24, 2023.The 13 full papers presented together with 8 doctoral symposium papers in this volume were carefully reviewed and selected from 34 submissions, the volume also contains one invited paper. The conference focuses on applying formal methods to practical applications and presents papers for research in all areas related to formal engineering methods.

Maschinelles Lernen (ML) ist zu einem alltäglichen Element in unserem Leben und zu einem Standardwerkzeug für viele Bereiche der Wissenschaft und Technik geworden. Um ML optimal nutzen zu können, ist es wichtig, die zugrunde liegenden Prinzipien zu verstehen. In diesem Buch wird ML als die rechnerische Umsetzung des wissenschaftlichen Prinzips betrachtet. Dieses Prinzip besteht darin, ein Modell eines gegebenen datenerzeugenden Phänomens kontinuierlich anzupassen, indem eine Form des Verlustes, der durch seine Vorhersagen entsteht, minimiert wird.Das Buch schult den Leser darin, verschiedene ML-Anwendungen und -Methoden in drei Komponenten (Daten, Modell und Verlust) aufzuschlüsseln, und hilft ihm so, aus dem riesigen Angebot an vorgefertigten ML-Methoden auszuwählen.Der Drei-Komponenten-Ansatz des Buches erlaubt eine einheitliche und transparente Darstellung verschiedener ML-Techniken. Wichtige Methoden zu Regularisierung, zum Schutz der Privatsphäre und zur Erklärbarkeit von ML-Methoden sind Spezialfälle dieses Drei-Komponenten-Ansatz.

This unique, accessible textbook gives a comprehensive introduction to software architecture, using ¿clean architecture¿ concepts with agile methods and model-driven development. The work introduces the key concepts of software architectures and explains the importance of architectural design for the long-term usefulness and sustainability of software systems. In addition, it describes more than 30 architectural styles and patterns that can be used for constructing mobile applications, enterprise and web applications, machine-learning systems, and safety-critical systems.Topics and features:Combines clean-architecture principles with agile model-driven developmentEmploys practical examples and real industrial cases to illustrate architectures for mobile apps, web apps, enterprise systems, safety-critical systems and machine-learning systemsExplores support tools for architectural design and system development using the approachProvides tutorial questions and slides to support teaching and learningDelivers material that has been class-tested over 10 years with more than 1,000 studentsThe textbook can be used to support teaching of an undergraduate module in software architecture, yet also includes more advanced topics suitable for a specialised software architecture module at master¿s level. It also will be eminently suitable and relevant for software practitioners and researchers needing or wanting to explore the field in short courses or self-study.Dr. Kevin Lano is Reader in Software Engineering, Department of Informatics, King's College London, UK. Dr. Sobhan Yassipour Tehrani is a Lecturer, Department of Computer Science, University College London, UK.

This book constitutes refereed proceedings of the 22nd International Conference on Mathematical Optimization Theory and Operations Research: Recent Trends, MOTOR 2023, held in Ekaterinburg, Russia, during July 2¿8, 2023. The 28 full papers and one invited paper presented in this volume were carefully reviewed and selected from a total of 61 submissions. The papers in the volume are organized according to the following topical headings: mathematical programming; stochastic optimization; discrete and combinatorial optimization; operations research; optimal control and mathematical economics; and optimization in machine learning.

This book constitutes the refereed conference proceedings of the 14th International Conference on Bio-inspired Information and Communications Technologies, held in Okinawa, Japan, during April 11-12, 2023. The 17 full papers were carefully reviewed and selected from 33 submissions. The papers focus on the latest research that leverages the understanding of key principles, processes, and mechanisms in biological systems for development of novel information and communications technologies (bio-inspired ICT). BICT 2023 will also highlight innovative research and technologies being developed for biomedicine that are inspired by ICT (ICT-inspired biomedicine).

This book constitutes the refereed proceedings of the 22nd International TRIZ Future Conference on Automated Invention for Smart Industries, TFC 2022, which took place in Warsaw, Poland, in September 2022; the event was sponsored by IFIP WG 5.4.The 39 full papers presented were carefully reviewed and selected from 43 submissions. They are organized in the following thematic sections: New perspectives of TRIZ; AI in systematic innovation; systematic innovations supporting IT and AI; TRIZ applications; TRIZ education and ecosystem.

This book constitutes proceedings of the 18th European Conference on Logics in Artificial Intelligence, JELIA 2023, held in Dresden, Germany, in September 2023.The 41 full papers and 11 short papers included in this volume were carefully reviewed and selected from 111 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).

This volume constitutes the thoroughly refereed proceedings of the 49th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2023. The 33 full papers presented in this volume were carefully reviewed and selected from a total of 116 submissions. The WG 2022 workshop aims to merge theory and practice by demonstrating how concepts from graph theory can be applied to various areas in computer science, or by extracting new graph theoretic problems from applications.

This volume LNCS 14240 constitutes the refereed proceedings of the 30th International Symposium on String Processing and Information Retrieval, SPIRE 2023, held in Pisa, Italy, during September 26¿28, 2023. The 31 full papers presented were carefully reviewed and selected from 47 submissions. They cover topics such as: data structures; algorithms; constrained Substring complexity; data compression codes; succinct k-spectra; and LCP array of wheeler DFAs.

This book covers recent developments in the understanding, quantification, and exploitation of entanglement in spin chain models from both condensed matter and quantum information perspectives. Spin chain models are at the foundation of condensed matter physics and quantum information technologies and elucidate many fundamental phenomena such as information scrambling, quantum phase transitions, and many-body localization. Moreover, many quantum materials and emerging quantum devices are well described by spin chains. Comprising accessible, self-contained chapters written by leading researchers, this book is essential reading for graduate students and researchers in quantum materials and quantum information.  The coverage is comprehensive, from the fundamental entanglement aspects of quantum criticality, non-equilibrium dynamics, classical and quantum simulation of spin chains through to their experimental realizations, and beyond into machine learning applications.

This book constitutes the proceedings of the 28th International Conference on Formal Methods for Industrial Critical Systems, FMICS 2023, held in Antwerp, Belgium, during September 20¿22, 2023.The 14 full papers included in this book were carefully reviewed and selected from 24 submissions. The papers focus on development and application of formal methods in industry. FMICS is a platform for scientists and engineers who are active in the area of formal methods and interested in exchanging their experiences in the industrial usage of these methods. FMICS also strives to promote research and development for the improvement of formal methods and tools for industrial applications.

Artificial Intelligence has revolutionised areas of medicine. This book focuses on the integral role of AI in radiology, shedding light on how this technology can enhance patient care and streamline professional workflows.

Learn to write algorithms and program in the new field of quantum computing. This second edition is updated to equip you with the latest knowledge and tools needed to be a complex problem-solver in this ever-evolving landscape. The book has expanded its coverage of current and future advancements and investments by IT companies in this emerging technology. Most chapters are thoroughly revised to incorporate the latest updates to IBM Quantum's systems and offerings, such as improved algorithms, integrating hardware advancements, software enhancements, bug fixes, and more. Yoüll examine quantum computing in the cloud and run experiments there on a real quantum device. Along the way yoüll cover game theory with the Magic Square, an example of quantum pseudo-telepathy. Yoüll also learn to write code using QISKit, Python SDK, and other APIs such as QASM and execute it against simulators (local or remote) or a real quantum computer. Then peek inside the inner workings of the Bell states for entanglement, Grover¿s algorithm for linear search, Shor¿s algorithm for integer factorization, and other algorithms in the fields of optimization, and more. Finally, yoüll learn the current quantum algorithms for entanglement, random number generation, linear search, integer factorization, and others. By the end of this book, yoüll understand how quantum computing provides massive parallelism and significant computational speedups over classical computersWhat You'll LearnWrite algorithms that provide superior performance over their classical counterpartsCreate a quantum number generator: the quintessential coin flip with a quantum twistExamine the quantum algorithms in use today for random number generation, linear search, and moreDiscover quantum teleportationHandle the counterfeit coin problem, a classic puzzle Put your knowledge to the testwith more than 150 practice exercises Who This Book Is ForDevelopers, programmers, computer science researchers, teachers, and students.

Synthetic Symmetry: A New Approach to Lie Theory" takes readers on an intellectual journey into the fascinating world of abstract algebra and its applications in modern mathematics and science. This groundbreaking book introduces a fresh perspective on Lie theory, a field renowned for its profound insights into symmetries, transformations, and the fundamental structure of mathematical objects.With clarity and precision, this book presents the innovative concept of "synthetic symmetry," offering a unique framework for understanding and exploring the intricate symmetries that permeate the mathematical universe. It reimagines traditional Lie theory, providing a more intuitive and accessible approach that appeals to both seasoned mathematicians and those new to the field.Through compelling explanations, insightful examples, and practical applications, "Synthetic Symmetry" demonstrates how this novel perspective can shed new light on a wide range of mathematical problems and scientific phenomena. Whether you are a mathematics enthusiast, a student, or a professional mathematician, this book will expand your understanding of symmetries and their role in shaping the mathematical and physical world.This book is an indispensable resource for anyone seeking a deeper appreciation of symmetry and its significance in mathematics, physics, and beyond. It challenges conventional thinking and invites readers to explore the beauty and elegance of synthetic symmetry, making it an essential addition to the library of anyone passionate about the mathematical sciences.

This book constitutes the proceedings of the 20th International Conference on Quantitative Evaluation of Systems, QEST 2023, which took place in Antwerp, Belgium, in September 2023. The 23 papers included in this book were carefully reviewed and selected from 44 submissions. They deal with current topics in quantitative evaluation and verification of computer systems and networks, focusing on data-driven and machine-learning systems, case studies, and tool papers. The book also contains the extended abstract of the invited talk from David Parker.

This proceedings volume gathers selected, revised papers presented at the 51st Southeastern International Conference on Combinatorics, Graph Theory and Computing (SEICCGTC 2020), held at Florida Atlantic University in Boca Raton, USA, on March 9-13, 2020. The SEICCGTC is broadly considered to be a trendsetter for other conferences around the world - many of the ideas and themes first discussed at it have subsequently been explored at other conferences and symposia.The conference has been held annually since 1970, in Baton Rouge, Louisiana and Boca Raton, Florida. Over the years, it has grown to become the major annual conference in its fields, and plays a major role in disseminating results and in fostering collaborative work.This volume is intended for the community of pure and applied mathematicians, in academia, industry and government, working in combinatorics and graph theory, as well as related areas of computer science and the interactions among these fields.

Beginning user level

This book constitutes the refereed proceedings of the 46th German Conference on Artificial Intelligence, KI 2023, which took place in Berlin, Germany, in September 2023.The 14 full and 5 short papers presented were carefully reviewed and selected from 78 submissions. The papers deal with research on theory and applications across all methods and topic areas of AI research.

This book constitutes the refereed proceedings of the 15th International Conference on Flexible Query Answering Systems, FQAS 2023, held in September 2023 in Palma de Mallorca, Spain. The 24 full papers presented were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: Flexible Queries over Semantic Systems; Advanced Methods and Applications in Natural Language; Processing (NLP); New Advances in Disinformation Detection; Data and Text Mining; Applying AI to Social Science and Social Science to AI; Artificial Intelligence Law and Regulation.

This volume LNCS 14127 constitutes the refereed proceedings of the 5th International Workshop, EXTRAAMAS 2023, held in London, UK, in May 2023. The 15 full papers presented together with 1 short paper were carefully reviewed and selected from 26 submissions. The workshop focuses on Explainable Agents and multi-agent systems; Explainable Machine Learning; and Cross-domain applied XAI.

To date, processing of high-throughput Mass Spectrometry (MS) data is accomplished using serial algorithms. Developing new methods to process MS data is an active area of research but there is no single strategy that focuses on scalability of MS based methods.  Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and metabolites in complex biological mixtures. In the recent years the technology has rapidly evolved and is now capable of generating increasingly large (multiple tera-bytes per experiment) and complex (multiple species/microbiome/high-dimensional) data sets. This rapid advance in MS instrumentation  must  be matched by equally fast and rapid evolution of scalable methods developed for analysis of these complex data sets. Ideally, the new methods should leverage the rich heterogeneous computational resources available in a ubiquitous fashion in the form of  multicore,  manycore,  CPU-GPU, CPU-FPGA, and IntelPhi architectures.  The absence of these high-performance computing algorithms now hinders scientific advancements for mass spectrometry research. In this book we illustrate the need for high-performance computing algorithms for MS based proteomics, and proteogenomics and showcase our progress in developing these high-performance algorithms.

This book presents a comprehensive study covering the design and application of models and algorithms for assessing the joint device failures of telecommunication backbone networks caused by large-scale regional disasters. At first, failure models are developed to make use of the best data available; in turn, a set of fast algorithms for determining the resulting failure lists are described; further, a theoretical analysis of the complexity of the algorithms and the properties of the failure lists is presented, and relevant practical case studies are investigated. Merging concepts and tools from complexity theory, combinatorial and computational geometry, and probability theory, a comprehensive set of models is developed for translating the disaster hazard in informative yet concise data structures. The information available on the network topology and the disaster hazard is then used to calculate the possible (probabilistic) network failures. The resulting sets of resources that are expected to break down simultaneously are modeled as a collection of Shared Risk Link Groups (SRLGs), or Probabilistic SRLGs. Overall, this book presents improved theoretical methods that can help predicting disaster-caused network malfunctions, identifying vulnerable regions, and assessing precisely the availability of internet services, among other applications.

This book is a hands-on guide for programmers who want to learn how C++ is used to develop solutions for options and derivatives trading in the financial industry. It explores the main algorithms and programming techniques used in implementing systems and solutions for trading options and derivatives. This updated edition will bring forward new advances in C++ software language and libraries, with a particular focus on the new C++23 standard.The book starts by covering C++ language features that are frequently used to write financial software for options and derivatives. These features include the STL (standard template library), generic templates, functional programming, and support for numerical code. Examples include additional support for lambda functions with simplified syntax, improvements in automatic type detection for templates, custom literals, modules, constant expressions, and improved initialization strategies for C++ objects. This book also provides how-to examples that cover all the major tools and concepts used to build working solutions for quantitative finance. It discusses how to create bug-free and efficient applications, leveraging the knowledge of object-oriented and template-based programming. It has two new chapters covering backtesting option strategies and processing financial data.. It introduces the topics covered in the book in a logical and structured way, with lots of examples that will bring them to life.Options and Derivatives Programming in C++23 has been written with the goal of reaching readers who are looking for a concise, algorithms-based book that provides basic information through well-targeted examples and ready to use solutions.What You Will LearnGain insight into the fundamental challenges of the options and derivatives marketMaster the features of the C++ language used in quantitative financial programmingUnderstand quantitative finance algorithms for options and derivativesBuild pricing algorithms around the Black-Scholes model, and use binomial and differential equations methodsWho This Book Is ForProfessional developers who have some experience with the C++ language and would like to leverage that knowledge into financial software development.

Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problemsIncludes a new chapter on generative AI and large language models (LLMs) and building a pipeline that leverages LLMs using LangChainKey FeaturesThis second edition delves deeper into key machine learning topics, CI/CD, and system designExplore core MLOps practices, such as model management and performance monitoringBuild end-to-end examples of deployable ML microservices and pipelines using AWS and open-source toolsBook DescriptionThe Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field.The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift.Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques.With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning.What you will learnPlan and manage end-to-end ML development projectsExplore deep learning, LLMs, and LLMOps to leverage generative AIUse Python to package your ML tools and scale up your solutionsGet to grips with Apache Spark, Kubernetes, and RayBuild and run ML pipelines with Apache Airflow, ZenML, and KubeflowDetect drift and build retraining mechanisms into your solutionsImprove error handling with control flows and vulnerability scanningHost and build ML microservices and batch processes running on AWSWho this book is forThis book is designed for MLOps and ML engineers, data scientists, and software developers who want to build robust solutions that use machine learning to solve real-world problems. If you're not a developer but want to manage or understand the product lifecycle of these systems, you'll also find this book useful. It assumes a basic knowledge of machine learning concepts and intermediate programming experience in Python. With its focus on practical skills and real-world examples, this book is an essential resource for anyone looking to advance their machine learning engineering career.Table of ContentsIntroduction to ML EngineeringThe Machine Learning Development ProcessFrom Model to Model Factory Packaging UpDeployment Patterns and ToolsScaling UpDeep Learning, Generative AI, and LLMOps Building an Example ML MicroserviceBuilding an Extract, Transform, Machine Learning Use Case

This book constitutes the refereed proceedings of the 16th International Conference on Intelligent Computer Mathematics, CICM 2023, held in Cambridge, UK, in September 2023.The 14 full papers, 2 project/survey papers, 6 short papers, and 1 tool paper presented were carefully reviewed and selected from a total of 37 submissions. The papers focus on advances in formalization, automatic theorem proving and learning, search and classification, teaching and geometric reasoning, and logic and systems, among other topics.