Download or read book Dynamic Learning Networks written by Aldo Romano and published by Springer Science & Business Media. This book was released on 2009-05-28 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Learning Networks: Models and Cases in Action represents an attempt to provide a network perspective of organizational learning to drive dynamic competition through extended firm learning processes. This edited volume, contributed by worldwide experts in the field, provides academics and company managers with an extended view of organizational learning networks from real cases and different perspectives. Dynamic Learning Networks: Models and Cases in Action is based on the workshop, Managing Uncertainty and Competition through Dynamic Learning Networks. It was organized by the E-Business Management Section of Scuola Superiore ISUFI – University of Salento (Italy) – and held in Ostuni (Italy) in July 2008. Dynamic Learning Networks: Models and Cases in Action is designed for a professional audience, composed of researchers and practitioners working in corporate learning. This volume is also suitable for advanced-level students in computer science.
Download or read book Static and Dynamic Neural Networks written by Madan Gupta and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuronale Netze haben sich in vielen Bereichen der Informatik und künstlichen Intelligenz, der Robotik, Prozeßsteuerung und Entscheidungsfindung bewährt. Um solche Netze für immer komplexere Aufgaben entwickeln zu können, benötigen Sie solide Kenntnisse der Theorie statischer und dynamischer neuronaler Netze. Aneignen können Sie sie sich mit diesem Lehrbuch! Alle theoretischen Konzepte sind in anschaulicher Weise mit praktischen Anwendungen verknüpft. Am Ende jedes Kapitels können Sie Ihren Wissensstand anhand von Übungsaufgaben überprüfen.
Download or read book A Field Guide to Dynamical Recurrent Networks written by John F. Kolen and published by John Wiley & Sons. This book was released on 2001-01-15 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.
Download or read book Graph Neural Networks Foundations Frontiers and Applications written by Lingfei Wu and published by Springer Nature. This book was released on 2022-01-03 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.
Download or read book Neuronal Dynamics written by Wulfram Gerstner and published by Cambridge University Press. This book was released on 2014-07-24 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
Download or read book Dynamic Network Theory written by James D. Westaby and published by American Psychological Association (APA). This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social networks surround us. They are as diverse as a local community trying to help solve a neighborhood crime, a firm wondering how to streamline decision making, or a terrorist cell figuring out how to plan an attack without central coordination. This groundbreaking book explores social networks in formal and informal organizations, using a combination of approaches from social psychology, I/O psychology, organization/management science, social learning, and helping skills. A quantum advance over conventional social network analysis, Dynamic Network Theory examines how social networks articulate goals and generate social capital at various levels. Geared for researchers and practitioners, Dynamic Network Theory is also written for graduate students and advanced undergraduate students. Appendixes include primers on designing and analyzing dynamic network charts.
Download or read book Deterministic Learning Theory for Identification Recognition and Control written by Cong Wang and published by CRC Press. This book was released on 2018-10-03 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic Environments The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information Processing This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).
Download or read book Data Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Download or read book Interfirm Networks written by Josef Windsperger and published by Springer. This book was released on 2014-12-01 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The organization of interfirm networks, such as alliances, cooperatives, franchise and retail chains, has become an important research topic in the field of economics, marketing, strategic management, and organization theory. This book contributes to the literature on formal and informal inter-organizational governance by providing new insights on contract design, ownership, evolution of cooperation, role of social capital and performance in franchising networks; includes topics of loyalty, reputation and organizational form as well as performance of cooperatives, and discusses the relationship between formal and relational governance in alliances, governance structures of innovation activities, dynamics of interfirm conflicts, and network externalities and alliance formation.
Download or read book Learning among Regional Governments written by Carina Abreu and published by wbv Media GmbH & Company KG. This book was released on 2007-09-28 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Die sechs englischsprachigen Beiträge dokumentieren die Konzepte der von der EU im Rahmen von Prevalet geförderten internationalen Zusammenarbeit zwischen regionalen Regierungen im europäischen Raum sowie dem daraus resultierenden Aufbau eines Systems zur Unterstützung und Beschleunigung des Lern- und Innovationstransfers zwischen den europäischen Regionen. Das in diesem Kontext entwickelte, web-basierte Support-Netzwerk Soft Open Method of Coordination (SMOC) soll die Kooperation zwischen regionalen Regierungen in Weiterbildungsfragen vereinfachen und steht allen an Weiterbildung interessierten Institutionen als Plattform für Information und Austausch zur Verfügung. Der ergänzende Band "Tools for Policy Learning and Policy Transfer" (978-3-7639-3580-2) enthält das empirische Material, die methodische Durchführung und die Präsentation des entwickelten Support-Systems.
Download or read book Next Generation Wireless Networks Meet Advanced Machine Learning Applications written by Com?a, Ioan-Sorin and published by IGI Global. This book was released on 2019-01-25 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-evolving wireless technology industry is demanding new technologies and standards to ensure a higher quality of experience for global end-users. This developing challenge has enabled researchers to identify the present trend of machine learning as a possible solution, but will it meet business velocity demand? Next-Generation Wireless Networks Meet Advanced Machine Learning Applications is a pivotal reference source that provides emerging trends and insights into various technologies of next-generation wireless networks to enable the dynamic optimization of system configuration and applications within the fields of wireless networks, broadband networks, and wireless communication. Featuring coverage on a broad range of topics such as machine learning, hybrid network environments, wireless communications, and the internet of things; this publication is ideally designed for industry experts, researchers, students, academicians, and practitioners seeking current research on various technologies of next-generation wireless networks.
Download or read book Never Stop Learning written by Bradley R. Staats and published by Harvard Business Press. This book was released on 2018-05-15 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keep learning, or risk becoming irrelevant. It's a truism in today's economy: the only constant is change. Technological automation is making jobs less routine and more cognitively challenging. Globalization means you're competing with workers around the world. Simultaneously, the internet and other communication technologies have radically increased the potential impact of individual knowledge.The relentless dynamism of these forces shaping our lives has created a new imperative: we must strive to become dynamic learners. In every industry and sector, dynamic learners outperform their peers and realize higher impact and fulfillment by learning continuously and by leveraging that learning to build yet more knowledge. In Never Stop Learning, behavioral scientist and operations expert Bradley R. Staats describes the principles and practices that comprise dynamic learning and outlines a framework to help you become more effective as a lifelong learner. The steps include: Valuing failure Focusing on process, not outcome, and on questions, not answers Making time for reflection Learning to be true to yourself by playing to your strengths Pairing specialization with variety Treating others as learning partners Replete with the most recent research about how we learn as well as engaging stories that show how real learning happens, Never Stop Learning will become the operating manual for leaders, managers, and anyone who wants to keep thriving in the new world of work.
Download or read book Shake Up Learning written by Kasey Bell and published by . This book was released on 2018-03-05 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is the learning in your classroom static or dynamic? Shake Up Learning guides you through the process of creating dynamic learning opportunities-from purposeful planning and maximizing technology to fearless implementation.
Download or read book Learning Network Services for Professional Development written by Rob Koper and published by Springer Science & Business Media. This book was released on 2009-07-07 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: A "Learning Network" is a community of people who help each other to better understand and handle certain events and concepts in work or life. As a result – and sometimes also as an aim – participating in learning networks stimulates personal development, a better understanding of concepts and events, career development, and employability. "Learning Network Services" are Web services that are designed to facilitate the creation of distributed Learning Networks and to support the participants with various functions for knowledge exchange, social interaction, assessment and competence development in an effective way. The book presents state-of-the-art insights into the field of Learning Networks and Web-based services which can facilitate all kinds of processes within these networks.
Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Download or read book Knowledge Networks written by Denise Bedford and published by Emerald Group Publishing. This book was released on 2021-10-26 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Networks describes the role of networks in the knowledge economy, explains network structures and behaviors, walks the reader through the design and setup of knowledge network analyses, and offers a step by step methodology for conducting a knowledge network analysis.
Download or read book Network Embedding written by Cheng Yang and published by Morgan & Claypool Publishers. This book was released on 2021-03-25 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL) and the background and rise of network embeddings (NE). It introduces the development of NE techniques by presenting several representative methods on general graphs, as well as a unified NE framework based on matrix factorization. Afterward, it presents the variants of NE with additional information: NE for graphs with node attributes/contents/labels; and the variants with different characteristics: NE for community-structured/large-scale/heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions. Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.
