Learning Representation For Multi View Data Analysis

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Learning Representation for Multi-View Data Analysis

Zhengming Ding,Handong Zhao,Yun Fu
Learning Representation for Multi View Data Analysis Book PDF

Author : Zhengming Ding,Handong Zhao,Yun Fu
Publisher : Springer
Page : 268 pages
File Size : 47,9 Mb
Release : 2018-12-06
Category : Computers
ISBN : 9783030007348

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Learning Representation for Multi-View Data Analysis by Zhengming Ding,Handong Zhao,Yun Fu Pdf

This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Recent Advancements in Multi-View Data Analytics

Witold Pedrycz,Shyi-Ming Chen
Recent Advancements in Multi View Data Analytics Book PDF

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer Nature
Page : 346 pages
File Size : 52,9 Mb
Release : 2022-05-20
Category : Computers
ISBN : 9783030952396

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Recent Advancements in Multi-View Data Analytics by Witold Pedrycz,Shyi-Ming Chen Pdf

This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.

Robust Representation for Data Analytics

Sheng Li,Yun Fu
Robust Representation for Data Analytics Book PDF

Author : Sheng Li,Yun Fu
Publisher : Springer
Page : 224 pages
File Size : 41,6 Mb
Release : 2017-08-09
Category : Computers
ISBN : 9783319601762

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Robust Representation for Data Analytics by Sheng Li,Yun Fu Pdf

This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary. Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Recent Applications in Data Clustering

Harun Pirim
Recent Applications in Data Clustering Book PDF

Author : Harun Pirim
Publisher : BoD – Books on Demand
Page : 250 pages
File Size : 53,6 Mb
Release : 2018-08-01
Category : Computers
ISBN : 9781789235265

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Recent Applications in Data Clustering by Harun Pirim Pdf

Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.

Multi-aspect Learning

Richi Nayak,Khanh Luong
Multi aspect Learning Book PDF

Author : Richi Nayak,Khanh Luong
Publisher : Springer Nature
Page : 191 pages
File Size : 46,8 Mb
Release : 2023-08-28
Category : Computers
ISBN : 9783031335600

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Multi-aspect Learning by Richi Nayak,Khanh Luong Pdf

This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning. It covers state-of-the-art representation learning techniques for clustering and their applications in various domains. This is the first book to systematically review multi-aspect data learning, incorporating a range of concepts and applications. Additionally, it is the first to comprehensively investigate manifold learning for dimensionality reduction in multi-view data learning. The book presents the latest advances in matrix factorization, subspace clustering, spectral clustering and deep learning methods, with a particular emphasis on the challenges and characteristics of multi-aspect data. Each chapter includes a thorough discussion of state-of-the-art of multi-aspect data learning methods and important research gaps. The book provides readers with the necessary foundational knowledge to apply these methods to new domains and applications, as well as inspire new research in this emerging field.

Graph Representation Learning

William L. William L. Hamilton
Graph Representation Learning Book PDF

Author : William L. William L. Hamilton
Publisher : Springer Nature
Page : 141 pages
File Size : 54,6 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031015885

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Graph Representation Learning by William L. William L. Hamilton Pdf

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

AI 2023: Advances in Artificial Intelligence

Tongliang Liu,Geoff Webb,Lin Yue,Dadong Wang
AI 2023 Advances in Artificial Intelligence Book PDF

Author : Tongliang Liu,Geoff Webb,Lin Yue,Dadong Wang
Publisher : Springer Nature
Page : 574 pages
File Size : 42,7 Mb
Release : 2023-11-26
Category : Computers
ISBN : 9789819983889

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AI 2023: Advances in Artificial Intelligence by Tongliang Liu,Geoff Webb,Lin Yue,Dadong Wang Pdf

This two-volume set LNAI 14471-14472 constitutes the refereed proceedings of the 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, held in Brisbane, QLD, Australia during November 28 – December 1, 2023. The 23 full papers presented together with 59 short papers were carefully reviewed and selected from 213 submissions. They are organized in the following topics: computer vision; deep learning; machine learning and data mining; optimization; medical AI; knowledge representation and NLP; explainable AI; reinforcement learning; and genetic algorithm.

Design, User Experience, and Usability: Understanding Users and Contexts

Aaron Marcus,Wentao Wang
Design User Experience and Usability Understanding Users and Contexts Book PDF

Author : Aaron Marcus,Wentao Wang
Publisher : Springer
Page : 810 pages
File Size : 51,8 Mb
Release : 2017-06-28
Category : Computers
ISBN : 9783319586403

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Design, User Experience, and Usability: Understanding Users and Contexts by Aaron Marcus,Wentao Wang Pdf

The three-volume set LNCS 10288, 10289, and 10290 constitutes the proceedings of the 6th International Conference on Design, User Experience, and Usability, DUXU 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCII 2017, in Vancouver, BC, Canada, in July 2017, jointly with 14 other thematically similar conferences. The total of 1228 papers presented at the HCII 2017 conferences were carefully reviewed and selected from 4340 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of Human-Computer Interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The total of 168 contributions included in the DUXU proceedings were carefully reviewed and selected for inclusion in this three-volume set. LNCS 10288: The 56 papers included in this volume are organized in topical sections on design thinking and design philosophy; aesthetics and perception in design; user experience evaluation methods and tools; user centered design in the software development lifecycle; DUXU education and training. LNCS 10289: The 56 papers included in this volume are organized in topical sections on persuasive and emotional design; mobile DUXU; designing the playing experience; designing the virtual, augmented and tangible experience; wearables and fashion technology. LNCS 10290: The 56 papers included in this volume are organized in topical sections on information design; understanding the user; DUXU for children and young users; DUXU for art, culture, tourism and environment; DUXU practice and case studies.

Prediction and Analysis for Knowledge Representation and Machine Learning

Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar
Prediction and Analysis for Knowledge Representation and Machine Learning Book PDF

Author : Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar
Publisher : CRC Press
Page : 232 pages
File Size : 42,9 Mb
Release : 2022-01-31
Category : Computers
ISBN : 9781000484212

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Prediction and Analysis for Knowledge Representation and Machine Learning by Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar Pdf

A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which includes both basic and advanced concepts.

Big Data Analytics and Knowledge Discovery

Min Song,Il-Yeol Song,Gabriele Kotsis,A Min Tjoa,Ismail Khalil
Big Data Analytics and Knowledge Discovery Book PDF

Author : Min Song,Il-Yeol Song,Gabriele Kotsis,A Min Tjoa,Ismail Khalil
Publisher : Springer Nature
Page : 413 pages
File Size : 46,6 Mb
Release : 2020-09-10
Category : Computers
ISBN : 9783030590659

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Big Data Analytics and Knowledge Discovery by Min Song,Il-Yeol Song,Gabriele Kotsis,A Min Tjoa,Ismail Khalil Pdf

The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.

Machine Learning and Data Analytics for Solving Business Problems

Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui
Machine Learning and Data Analytics for Solving Business Problems Book PDF

Author : Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui
Publisher : Springer Nature
Page : 214 pages
File Size : 55,7 Mb
Release : 2022-12-15
Category : Technology & Engineering
ISBN : 9783031184833

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Machine Learning and Data Analytics for Solving Business Problems by Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui Pdf

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

MOBIMEDIA 2020

Lin Yun,Tu Ya,Wang Meiyu
MOBIMEDIA 2020 Book PDF

Author : Lin Yun,Tu Ya,Wang Meiyu
Publisher : European Alliance for Innovation
Page : 1259 pages
File Size : 55,9 Mb
Release : 2020-11-19
Category : Social Science
ISBN : 9781631902710

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MOBIMEDIA 2020 by Lin Yun,Tu Ya,Wang Meiyu Pdf

We are delighted to introduce the proceedings of the 13th edition of the 2020 European Alliance for Innovation (EAI) International Conference on Mobile Multimedia Communications (MOBIMEDIA). This conference has brought researchers, developers and practitioners around the world who are leveraging and developing multimedia coding, mobile communications and networking fields. Developing and leveraging multimedia coding, mobile communications and networking fields requires adopting an interdisciplinary approach where multimedia, networking and physical layer issues are addressed jointly. Basic theories, key technologies and Artificial Intelligence for next-generations wireless communications，intelligent technologies for subspace learning and clustering of high-dimensional data, security and safety, communication networks and coding analysis, electromagnetic and media access control, D2D and IoT, multimedia platform and analysis, new energy and smart city, vision and images analysis, systems and applications, case studies and prediction and educational application are research challenges that need to be carefully examined when designing new mobile media architectures. We also need to put a great effort in designing applications that take into account the way the user perceives the overall quality of the provided service. Within this scope, the MOBIMEDIA 2020 was intended to provide a unique international forum for researchers from industry and academia to study new technologies, applications and standards. Original unpublished contributions are solicited that can improve the knowledge and practice in the integrated design of efficient technologies and the relevant provision of advanced mobile multimedia applications.

Prediction and Analysis for Knowledge Representation and Machine Learning

Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar
Prediction and Analysis for Knowledge Representation and Machine Learning Book PDF

Author : Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar
Publisher : CRC Press
Page : 216 pages
File Size : 55,5 Mb
Release : 2022-01-31
Category : Computers
ISBN : 9781000484229

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Prediction and Analysis for Knowledge Representation and Machine Learning by Avadhesh Kumar,Shrddha Sagar,T Ganesh Kumar,K Sampath Kumar Pdf

A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which includes both basic and advanced concepts.

Recent Developments in Mechatronics and Intelligent Robotics

Kevin Deng,Zhengtao Yu,Srikanta Patnaik,John Wang
Recent Developments in Mechatronics and Intelligent Robotics Book PDF

Author : Kevin Deng,Zhengtao Yu,Srikanta Patnaik,John Wang
Publisher : Springer
Page : 1280 pages
File Size : 55,5 Mb
Release : 2018-10-04
Category : Technology & Engineering
ISBN : 9783030002145

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Recent Developments in Mechatronics and Intelligent Robotics by Kevin Deng,Zhengtao Yu,Srikanta Patnaik,John Wang Pdf

This book is a collection of proceedings of the International Conference on Mechatronics and Intelligent Robotics (ICMIR2018), held in Kunming, China during May 19–20, 2018. It consists of 155 papers, which have been categorized into 6 different sections: Intelligent Systems, Robotics, Intelligent Sensors & Actuators, Mechatronics, Computational Vision and Machine Learning, and Soft Computing. The volume covers the latest ideas and innovations both from the industrial and academic worlds, as well as shares the best practices in the fields of mechanical engineering, mechatronics, automatic control, IOT and its applications in industry, electrical engineering, finite element analysis and computational engineering. The volume covers key research outputs, which delivers a wealth of new ideas and food for thought to the readers.

Internet Multimedia Computing and Service

Benoit Huet,Liqiang Nie,Richang Hong
Internet Multimedia Computing and Service Book PDF

Author : Benoit Huet,Liqiang Nie,Richang Hong
Publisher : Springer
Page : 496 pages
File Size : 55,5 Mb
Release : 2018-02-28
Category : Computers
ISBN : 9789811085307

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Internet Multimedia Computing and Service by Benoit Huet,Liqiang Nie,Richang Hong Pdf

This book constitutes the refereed proceedings of the 9th International Conference on Internet Multimedia Computing and Service, ICIMCS 2017, held in Qingdao, China, in August 2017. The 20 revised full papers and 28 revised short papers presented were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections on multimedia information fusion, image processing and object recognition, machine learning and representation learning, multimedia retrieval, poster papers.