Irwin King – författare

For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis.

For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis.

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The second volume, LNCS 12533, is organized in topical sections on computational intelligence; machine learning; robotics and control.

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.

This book constitutes the refereed proceedings of the 9th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2021, held in December 2021. Due to COVID-19 pandemic the conference was held virtually.

The 62 full papers included in this book were carefully reviewed and selected from 215 submissions. They were organized in topical sections as follows: image processing; text, voice and video processing; bioinformatics; deep learning; medical image processing; theory and models; feature selection; biometrics and dermoscopy; facial image analysis; object and event detection; pattern recognition; machine learning applications.

The book is divided into three main parts - Part I: Overview of MOOCs introduces the origin and history of MOOCs and the development of MOOC platforms in Greater China and the global context; Part II: Key Issues discuss the MOOC policies, innovative pedagogy, technology, and ecosystems worldwide; and Part III: Beyond MOOCs probes into the roles and benefits of MOOCs in times of crises, as well as the outlook of MOOCs in the future.

In terms of topic diversity, the book contains a comprehensive investigation of the past and latest MOOC developments, extracting and elaborating on relevant information regarding platforms, policies, pedagogy, technology, and ecosystems. Subsequently, in-depth analyses of MOOC data are utilized to deduce the current trends related to the MOOC movement and to extrapolate the likeliest direction of development for MOOCs in the years to come. The book can inform policymakers, education institutions, course instructors, platform developers, investors, researchers, and individual learners of MOOCs about critical information on the present and future of MOOC development, assisting them in making crucial decisions on what initiatives can optimize their advantages in the sector.

This LNAI volume constitutes the post proceedings of International Federated Learning Workshops such as follows:

FL@FM-WWW 2024, FL@FM-ICME 2024, FL@FM-IJCAI 2024 and FL@FM-NeurIPS 2024. This LNAI volume focuses on the following topics:

Efficient Model Adaptation and Personalization, Data Heterogeneity and Incomplete Data, Integration of Specialized Neural Architectures, Frameworks and Tools for Federated Learning, Applications in Domain-Specific Contexts, Unsupervised and Lightweight Learning, and Causal Discovery and Black-Box Optimization.

Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications.

Kaizhu Huang was a researcher at the Fujitsu Research and Development Center and is currently a research fellow in the Chinese University of Hong Kong. Haiqin Yang leads the image processing group at HiSilicon Technologies. Irwin King and Michael R. Lyu are professors at the Computer Science and Engineering departmentof the Chinese University of Hong Kong.

Ever since its inception, the Web has changed the landscape of human experiences on how we interact with one another and data through service infrastructures via various computing devices. This interweaving environment is now becoming ever more embedded into devices and systems that integrate seamlessly on how we live, both in our working or leisure time. For this volume, King and Baeza-Yates selected some pioneering and cutting-edge research work that is pointing to the future of the Web. Based on the Workshop Track of the 17th International World Wide Web Conference (WWW2008) in Beijing, they selected the top contributions and asked the authors to resubmit their work with a minimum of one third of additional material from their original workshop manuscripts to be considered for this volume. After a second-round of reviews and selection, 16 contributions were finally accepted. The work within this volume represents the tip of an iceberg of the many exciting advancements on the WWW. It covers topics like semantic web services, location-based and mobile applications, personalized and context-dependent user interfaces, social networks, and folksonomies. The presentations aim at researchers in academia and industry by showcasing latest research findings. Overall they deliver an excellent picture of the current state-of-the-art, and will also serve as the basis for ongoing research discussions and point to new directions.