Scalable and Distributed Machine Learning and Deep Learning Patterns

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Publisher : IGI Global
ISBN 13 : 1668498057
Total Pages : 315 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Scalable and Distributed Machine Learning and Deep Learning Patterns by : Thomas, J. Joshua

Download or read book Scalable and Distributed Machine Learning and Deep Learning Patterns written by Thomas, J. Joshua and published by IGI Global. This book was released on 2023-08-25 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scalable and Distributed Machine Learning and Deep Learning Patterns is a practical guide that provides insights into how distributed machine learning can speed up the training and serving of machine learning models, reduce time and costs, and address bottlenecks in the system during concurrent model training and inference. The book covers various topics related to distributed machine learning such as data parallelism, model parallelism, and hybrid parallelism. Readers will learn about cutting-edge parallel techniques for serving and training models such as parameter server and all-reduce, pipeline input, intra-layer model parallelism, and a hybrid of data and model parallelism. The book is suitable for machine learning professionals, researchers, and students who want to learn about distributed machine learning techniques and apply them to their work. This book is an essential resource for advancing knowledge and skills in artificial intelligence, deep learning, and high-performance computing. The book is suitable for computer, electronics, and electrical engineering courses focusing on artificial intelligence, parallel computing, high-performance computing, machine learning, and its applications. Whether you're a professional, researcher, or student working on machine and deep learning applications, this book provides a comprehensive guide for creating distributed machine learning, including multi-node machine learning systems, using Python development experience. By the end of the book, readers will have the knowledge and abilities necessary to construct and implement a distributed data processing pipeline for machine learning model inference and training, all while saving time and costs.

Machine Learning and Wireless Communications

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Publisher : Cambridge University Press
ISBN 13 : 1108967736
Total Pages : 560 pages
Book Rating : 4.1/5 (89 download)

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Book Synopsis Machine Learning and Wireless Communications by : Yonina C. Eldar

Download or read book Machine Learning and Wireless Communications written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2022-06-30 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Wireless Algorithms, Systems, and Applications

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Publisher : Springer Nature
ISBN 13 : 3030859282
Total Pages : 635 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Wireless Algorithms, Systems, and Applications by : Zhe Liu

Download or read book Wireless Algorithms, Systems, and Applications written by Zhe Liu and published by Springer Nature. This book was released on 2021-09-08 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 12937 - 12939 constitutes the proceedings of the 16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021, which was held during June 25-27, 2021. The conference took place in Nanjing, China.The 103 full and 57 short papers presented in these proceedings were carefully reviewed and selected from 315 submissions. The following topics are covered in Part I of the set: network protocols, signal processing, wireless telecommunication systems, blockchain, IoT and edge computing, artificial intelligence, computer security, distributed computer systems, machine learning, and others.

Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing

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Publisher : IGI Global
ISBN 13 : 1799853403
Total Pages : 2700 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing by : Management Association, Information Resources

Download or read book Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-01-25 with total page 2700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. The Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing is a vital reference source that provides valuable insight into current and emergent research occurring within the field of distributed computing. It also presents architectures and service frameworks to achieve highly integrated distributed systems and solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting a range of topics such as data sharing, wireless sensor networks, and scalability, this multi-volume book is ideally designed for system administrators, integrators, designers, developers, researchers, academicians, and students.

Microelectronics, Communication Systems, Machine Learning and Internet of Things

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Publisher : Springer Nature
ISBN 13 : 9811919062
Total Pages : 698 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Microelectronics, Communication Systems, Machine Learning and Internet of Things by : Vijay Nath

Download or read book Microelectronics, Communication Systems, Machine Learning and Internet of Things written by Vijay Nath and published by Springer Nature. This book was released on 2022-07-11 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents peer-reviewed papers of the First International Conference on Microelectronics, Communication Systems, Machine Learning, and the Internet of Things (MCMI-2020). This book discusses recent trends in technology and advancement in microelectronics, nano-electronics, VLSI design, IC technologies, wireless communications, optical communications, SoC, advanced instrumentations, signal processing, internet of things, machine learning, image processing, green energy, hybrid vehicles, weather forecasting, cloud computing, renewable energy, CMOS sensors, actuators, RFID, transducers, real-time embedded system, sensor network and applications, EDA design tools and techniques, fuzzy logic & artificial intelligence, high-performance computer architecture, AI-based robotics & applications, brain-computer interface, deep learning, advanced operating systems, supply chain development & monitoring, physical systems design, ICT applications, e-farming, information security, etc. It includes original papers based on theoretical, practical, experimental, simulations, development, application, measurement, and testing. The applications and solutions discussed in the book will serve as good reference material for young scholars, researchers, and academics.

The 13th Conference on Information Technology and Its Applications

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Publisher : Springer Nature
ISBN 13 : 3031741277
Total Pages : 559 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis The 13th Conference on Information Technology and Its Applications by : Ngoc Thanh Nguyen

Download or read book The 13th Conference on Information Technology and Its Applications written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Wired / Wireless Internet Communication

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Publisher : Springer
ISBN 13 : 3642306306
Total Pages : 394 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Wired / Wireless Internet Communication by : Yevgeni Koucheryavy

Download or read book Wired / Wireless Internet Communication written by Yevgeni Koucheryavy and published by Springer. This book was released on 2012-05-17 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Wired / Wireless Internet Communications, WWIC, held in Santorini island, Greece during June 6-8, 2012. The 23 revised full papers and 6 short papers presented were carefully reviewed and selected from 50 submissions. The papers are organized in six thematically-distinct technical sessions, covering the following major topics: virtual networks and clouds, multimedia systems, wireless sensor networks and localization, delay-tolerant and opportunistic networks, handover techniques and channel access, and ad hoc networks

Federated Learning: From Algorithms To System Implementation

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Publisher : World Scientific
ISBN 13 : 9811292566
Total Pages : 546 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Federated Learning: From Algorithms To System Implementation by : Liefeng Bo

Download or read book Federated Learning: From Algorithms To System Implementation written by Liefeng Bo and published by World Scientific. This book was released on 2024-08-16 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Authored by researchers and practitioners who build cutting-edge federated learning applications to solve real-world problems, this book covers the spectrum of federated learning technology from concepts and application scenarios to advanced algorithms and finally system implementation in three parts. It provides a comprehensive review and summary of federated learning technology, as well as presenting numerous novel federated learning algorithms which no other books have summarized. The work also references the most recent papers, articles and reviews from the past several years to keep pace with the academic and industrial state of the art of federated learning.The first part lays a foundational understanding of federated learning by going through its definition and characteristics, and also possible application scenarios and related privacy protection technologies. The second part elaborates on some of the federated learning algorithms innovated by JD Technology which encompass both vertical and horizontal scenarios, including vertical federated tree models, linear regression, kernel learning, asynchronous methods, deep learning, homomorphic encryption, and reinforcement learning. The third and final part shifts in scope to federated learning systems — namely JD Technology's own FedLearn system — by discussing its design and implementation using gRPC, in addition to specific performance optimization techniques plus integration with blockchain technology.This book will serve as a great reference for readers who are experienced in federated learning algorithms, building privacy-preserving machine learning applications or solving real-world problems with privacy-restricted scenarios.

ECAI 2023

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Publisher : IOS Press
ISBN 13 : 164368437X
Total Pages : 3328 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis ECAI 2023 by : K. Gal

Download or read book ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.

Machine Learning via Rust

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Author :
Publisher : RantAI
ISBN 13 :
Total Pages : 131 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning via Rust by : Evan Pradipta Hardinatha

Download or read book Machine Learning via Rust written by Evan Pradipta Hardinatha and published by RantAI. This book was released on 2024-10-14 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform Machine Learning with Rust! 🤖🦀 Introducing MLVR - Machine Learning via Rust—the groundbreaking textbook that seamlessly blends the theoretical rigor of machine learning with the modern, high-performance capabilities of the Rust programming language! 🚀 Whether you're a student embarking on your machine learning journey or a professional looking to elevate your skills, MLVR is your comprehensive guide to mastering machine learning with Rust’s unparalleled strengths in performance, safety, and concurrency. ✨ Why Choose MLVR? 🔍 Comprehensive Coverage: From classical models like linear regression and neural networks to cutting-edge techniques such as AutoML and reinforcement learning, MLVR covers it all. 💡 Modern Integration: Leverage Rust’s unique ownership model and advanced type system to implement machine learning algorithms with unmatched safety and efficiency. 🛠️ Practical Implementation: Benefit from step-by-step coding guides, clear explanations, and real-world applications that bridge the gap between theory and practice. 🤖 Performance & Safety: Harness Rust’s core strengths to build machine learning models that are not only fast but also memory-safe and concurrent. Unlock the Benefits: ✅ High Performance: Optimize machine learning models to run at peak speed using Rust’s low-level control without compromising on safety. ✅ Scalable Solutions: Implement scalable and efficient machine learning systems that can handle large datasets and complex computations. ✅ Robust Deployments: Deploy machine learning models with confidence, knowing that Rust’s strong type system and ownership model prevent common programming errors. What You'll Explore: Foundations of Machine Learning: Understand the essential concepts and algorithms that form the backbone of machine learning. Advanced Techniques: Dive into sophisticated methods like AutoML and reinforcement learning, tailored for Rust’s ecosystem. Real-World Applications: Apply your knowledge to real-world projects, showcasing the practical power of Rust in machine learning. Optimization Strategies: Learn how to fine-tune your models for maximum performance and efficiency using Rust’s capabilities. Perfect For: Students seeking a solid foundation in machine learning with a modern programming language. Professionals aiming to enhance their machine learning expertise and optimize their Rust projects. Developers of all levels who want to implement, optimize, and deploy machine learning models effectively using Rust. Embrace the future of machine learning—transform your skills and projects with MLVR - Machine Learning via Rust’s innovative and comprehensive approach! 📚🌟 Start your journey towards mastering machine learning with Rust today and unlock new possibilities in this rapidly evolving field! 🏆 #MachineLearning #RustProgramming #MLVR #DataScience #AI #TechBooks #LearnRust #DeveloperSkills #SoftwareEngineering

Federated Learning

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Publisher : Springer Nature
ISBN 13 : 3030630765
Total Pages : 291 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Federated Learning by : Qiang Yang

Download or read book Federated Learning written by Qiang Yang and published by Springer Nature. This book was released on 2020-11-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”

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Author :
Publisher : Springer Nature
ISBN 13 : 3031703596
Total Pages : 507 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis by :

Download or read book written by and published by Springer Nature. This book was released on with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Reliable and Secure Distributed Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 3642152600
Total Pages : 381 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Introduction to Reliable and Secure Distributed Programming by : Christian Cachin

Download or read book Introduction to Reliable and Secure Distributed Programming written by Christian Cachin and published by Springer Science & Business Media. This book was released on 2011-02-11 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes. Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance".

Edge Learning for Distributed Big Data Analytics

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Publisher : Cambridge University Press
ISBN 13 : 1108832377
Total Pages : 231 pages
Book Rating : 4.1/5 (88 download)

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Book Synopsis Edge Learning for Distributed Big Data Analytics by : Song Guo

Download or read book Edge Learning for Distributed Big Data Analytics written by Song Guo and published by Cambridge University Press. This book was released on 2022-02-10 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.

Euro-Par 2018: Parallel Processing

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Publisher : Springer
ISBN 13 : 3319969838
Total Pages : 849 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Euro-Par 2018: Parallel Processing by : Marco Aldinucci

Download or read book Euro-Par 2018: Parallel Processing written by Marco Aldinucci and published by Springer. This book was released on 2018-08-20 with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 24th International Conference on Parallel and Distributed Computing, Euro-Par 2018, held in Turin, Italy, in August 2018. The 57 full papers presented in this volume were carefully reviewed and selected from 194 submissions. They were organized in topical sections named: support tools and environments; performance and power modeling, prediction and evaluation; scheduling and load balancing; high performance architecutres and compilers; parallel and distributed data management and analytics; cluster and cloud computing; distributed systems and algorithms; parallel and distributed programming, interfaces, and languages; multicore and manycore methods and tools; theory and algorithms for parallel computation and networking; parallel numerical methods and applications; and accelerator computing for advanced applications.

Meta-Heuristic Algorithms for Advanced Distributed Systems

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Publisher : John Wiley & Sons
ISBN 13 : 1394188064
Total Pages : 469 pages
Book Rating : 4.3/5 (941 download)

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Book Synopsis Meta-Heuristic Algorithms for Advanced Distributed Systems by : Rohit Anand

Download or read book Meta-Heuristic Algorithms for Advanced Distributed Systems written by Rohit Anand and published by John Wiley & Sons. This book was released on 2024-04-02 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: META-HEURISTIC ALGORITHMS FOR ADVANCED DISTRIBUTED SYSTEMS Discover a collection of meta-heuristic algorithms for distributed systems in different application domains Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems—generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly. Meta-Heuristic Algorithms for Advanced Distributed Systems offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable. Meta-Heuristic Algorithms for Advanced Distributed Systems readers will also find: Analysis of security issues, distributed system design, stochastic optimization techniques, and more Detailed discussion of meta-heuristic techniques such as the genetic algorithm, particle swam optimization, and many others Applications of optimized distribution systems in healthcare and other key??industries Meta-Heuristic Algorithms for Advanced Distributed Systems is ideal for academics and researchers studying distributed systems, their design, and their applications.

Intelligent Systems

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Publisher : Springer Nature
ISBN 13 : 303121689X
Total Pages : 686 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Intelligent Systems by : João Carlos Xavier-Junior

Download or read book Intelligent Systems written by João Carlos Xavier-Junior and published by Springer Nature. This book was released on 2022-11-18 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13653 and 13654 constitutes the refereed proceedings of the 11th Brazilian Conference on Intelligent Systems, BRACIS 2022, which took place in Campinas, Brazil, in November/December 2022. The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence.