Geometric Structure Of High Dimensional Data And Dimensionality Reduction

Author : Jianzhong Wang
Publisher : Springer Science & Business Media
Page : 356 pages
File Size : 53,5 Mb
Release : 2012-04-28
Category : Computers
ISBN : 9783642274978

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Geometric Structure of High-Dimensional Data and Dimensionality Reduction by Jianzhong Wang Pdf

"Geometric Structure of High-Dimensional Data and Dimensionality Reduction" adopts data geometry as a framework to address various methods of dimensionality reduction. In addition to the introduction to well-known linear methods, the book moreover stresses the recently developed nonlinear methods and introduces the applications of dimensionality reduction in many areas, such as face recognition, image segmentation, data classification, data visualization, and hyperspectral imagery data analysis. Numerous tables and graphs are included to illustrate the ideas, effects, and shortcomings of the methods. MATLAB code of all dimensionality reduction algorithms is provided to aid the readers with the implementations on computers. The book will be useful for mathematicians, statisticians, computer scientists, and data analysts. It is also a valuable handbook for other practitioners who have a basic background in mathematics, statistics and/or computer algorithms, like internet search engine designers, physicists, geologists, electronic engineers, and economists. Jianzhong Wang is a Professor of Mathematics at Sam Houston State University, U.S.A.

Author : Zhongzhi Shi
Publisher : Springer Nature
Page : 518 pages
File Size : 43,9 Mb
Release : 2024-06-19
Category : Electronic
ISBN : 9783031578083

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Intelligent Information Processing XII by Zhongzhi Shi Pdf

Author : Benyamin Ghojogh,Mark Crowley,Fakhri Karray,Ali Ghodsi
Publisher : Springer Nature
Page : 617 pages
File Size : 53,5 Mb
Release : 2023-02-02
Category : Computers
ISBN : 9783031106026

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Elements of Dimensionality Reduction and Manifold Learning by Benyamin Ghojogh,Mark Crowley,Fakhri Karray,Ali Ghodsi Pdf

Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and manifold learning. Three main aspects of dimensionality reduction are covered: spectral dimensionality reduction, probabilistic dimensionality reduction, and neural network-based dimensionality reduction, which have geometric, probabilistic, and information-theoretic points of view to dimensionality reduction, respectively. The necessary background and preliminaries on linear algebra, optimization, and kernels are also explained to ensure a comprehensive understanding of the algorithms. The tools introduced in this book can be applied to various applications involving feature extraction, image processing, computer vision, and signal processing. This book is applicable to a wide audience who would like to acquire a deep understanding of the various ways to extract, transform, and understand the structure of data. The intended audiences are academics, students, and industry professionals. Academic researchers and students can use this book as a textbook for machine learning and dimensionality reduction. Data scientists, machine learning scientists, computer vision scientists, and computer scientists can use this book as a reference. It can also be helpful to statisticians in the field of statistical learning and applied mathematicians in the fields of manifolds and subspace analysis. Industry professionals, including applied engineers, data engineers, and engineers in various fields of science dealing with machine learning, can use this as a guidebook for feature extraction from their data, as the raw data in industry often require preprocessing. The book is grounded in theory but provides thorough explanations and diverse examples to improve the reader’s comprehension of the advanced topics. Advanced methods are explained in a step-by-step manner so that readers of all levels can follow the reasoning and come to a deep understanding of the concepts. This book does not assume advanced theoretical background in machine learning and provides necessary background, although an undergraduate-level background in linear algebra and calculus is recommended.

Author : Zhang Zhang,Kaiqi Huang
Publisher : Springer
Page : 167 pages
File Size : 54,9 Mb
Release : 2016-12-20
Category : Computers
ISBN : 9789811034763

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Intelligent Visual Surveillance by Zhang Zhang,Kaiqi Huang Pdf

This book constitutes the refereed proceedings of the 4th Chinese Conference, IVS 2016, held in Beijing, China, in October 2016. The 19 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on low-level preprocessing, surveillance systems; tracking, robotics; identification, detection, recognition; behavior, activities, crowd analysis.

Author : Mohammad Zoynul Abedin,M. Kabir Hassan,Petr Hajek,Mohammed Mohi Uddin
Publisher : Routledge
Page : 259 pages
File Size : 53,6 Mb
Release : 2021-06-20
Category : Business & Economics
ISBN : 9781000394115

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The Essentials of Machine Learning in Finance and Accounting by Mohammad Zoynul Abedin,M. Kabir Hassan,Petr Hajek,Mohammed Mohi Uddin Pdf

• A useful guide to financial product modeling and to minimizing business risk and uncertainty • Looks at wide range of financial assets and markets and correlates them with enterprises’ profitability • Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets • Real world applicable examples to further understanding

Author : James Bailey,Latifur Khan,Takashi Washio,Gill Dobbie,Joshua Zhexue Huang,Ruili Wang
Publisher : Springer
Page : 608 pages
File Size : 54,6 Mb
Release : 2016-04-11
Category : Computers
ISBN : 9783319317533

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Advances in Knowledge Discovery and Data Mining by James Bailey,Latifur Khan,Takashi Washio,Gill Dobbie,Joshua Zhexue Huang,Ruili Wang Pdf

This two-volume set, LNAI 9651 and 9652, constitutes the thoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed and selected from 307 submissions. They are organized in topical sections named: classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; feature extraction and pattern mining; graph and network data; spatiotemporal and image data; anomaly detection and clustering; novel models and algorithms; and text mining and recommender systems.

Author : Steve Y. Oudot
Publisher : American Mathematical Soc.
Page : 218 pages
File Size : 53,8 Mb
Release : 2017-05-17
Category : Electronic
ISBN : 9781470434434

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Persistence Theory: From Quiver Representations to Data Analysis by Steve Y. Oudot Pdf

Persistence theory emerged in the early 2000s as a new theory in the area of applied and computational topology. This book provides a broad and modern view of the subject, including its algebraic, topological, and algorithmic aspects. It also elaborates on applications in data analysis. The level of detail of the exposition has been set so as to keep a survey style, while providing sufficient insights into the proofs so the reader can understand the mechanisms at work. The book is organized into three parts. The first part is dedicated to the foundations of persistence and emphasizes its connection to quiver representation theory. The second part focuses on its connection to applications through a few selected topics. The third part provides perspectives for both the theory and its applications. The book can be used as a text for a course on applied topology or data analysis.

Author : Eklas Hossain
Publisher : Springer Nature
Page : 465 pages
File Size : 43,6 Mb
Release : 2023-12-26
Category : Computers
ISBN : 9783031469909

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Machine Learning Crash Course for Engineers by Eklas Hossain Pdf

​Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of machine learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement machine learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of machine learning quickly.

Author : Anonim
Publisher : DEStech Publications, Inc
Page : 1269 pages
File Size : 50,6 Mb
Release : 2014-01-07
Category : Medical
ISBN : 9781605951638

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2013 6th International Conference on BioMedical Engineering and Informatics (BMEI 2013) by Anonim Pdf

SPBEI 2013 aims to be an excellent platform to facilitate international exchange of state-ofthe- art research and practice in image, video, and signal processing, biomedical engineering, informatics, and their cross-intersection to catalyze innovative research ideas and to dissimilate new scientific discoveries. The nature of the research demands collaboration in medicine, biology, physics, engineering, computer science, and statistics; and SPBEI attempts to expedite and strengthen the exploration and systemization of interdisciplinary knowledge. This year, the conference received a large number of submissions around the globe, and all papers have been rigorously reviewed by a large number of peer reviewers who have spent tremendous amount of time and effort on the evaluations, with each paper receiving three to six reviews. We would like to thank all those who submitted papers for considerations, and we extend our sincere gratitude to all those who devoted their time and effort professionally to ensuring the high standards of the technical program, including the authors, committee members, peer reviewers, and session chairs.

Author : Kokula Krishna Hari K
Publisher : TECHNO FORUM R&D CENTRE
Page : 213 pages
File Size : 44,7 Mb
Release : 2024-06-19
Category : Electronic
ISBN : 9788192057590

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International Conference on Computer Applications 2012 :: Volume 06 by Kokula Krishna Hari K Pdf

Author : Fanzhang Li,Li Zhang,Zhao Zhang
Publisher : Walter de Gruyter GmbH & Co KG
Page : 593 pages
File Size : 43,9 Mb
Release : 2018-11-05
Category : Computers
ISBN : 9783110498073

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Lie Group Machine Learning by Fanzhang Li,Li Zhang,Zhao Zhang Pdf

This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artifi cial intelligence. The book further discusses algorithms and applications in tensor learning, spectrum estimation learning, Finsler geometry learning, Homology boundary learning, and prototype theory. With abundant case studies, this book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artifi cial intelligence, machine learning, automation, mathematics, management science, cognitive science, financial management, and data analysis. In addition, this text can be used as the basis for teaching the principles of machine learning. Li Fanzhang is professor at the Soochow University, China. He is director of network security engineering laboratory in Jiangsu Province and is also the director of the Soochow Institute of industrial large data. He published more than 200 papers, 7 academic monographs, and 4 textbooks. Zhang Li is professor at the School of Computer Science and Technology of the Soochow University. She published more than 100 papers in journals and conferences, and holds 23 patents. Zhang Zhao is currently an associate professor at the School of Computer Science and Technology of the Soochow University. He has authored and co-authored more than 60 technical papers.

Author : Marzena Kryszkiewicz,Chris Cornelis,Davide Ciucci,Jesús Medina-Moreno,Hiroshi Motoda,Zbigniew Ras
Publisher : Springer
Page : 394 pages
File Size : 45,9 Mb
Release : 2014-06-13
Category : Computers
ISBN : 9783319087290

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Rough Sets and Intelligent Systems Paradigms by Marzena Kryszkiewicz,Chris Cornelis,Davide Ciucci,Jesús Medina-Moreno,Hiroshi Motoda,Zbigniew Ras Pdf

This book constitutes the refereed proceedings of the 23rd Australasian Joint Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2014, held in Granada and Madrid, Spain, in July 2014. RSEISP 2014 was held along with the 9th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2014, as a major part of the 2014 Joint Rough Set Symposium, JRS 2014. JRS 2014 received 40 revised full papers and 37 revised short papers which were carefully reviewed and selected from 120 submissions and presented in two volumes. This volume contains the papers accepted for the conference RSEISP 2014, as well as the three invited papers presented at the conference. The papers are organized in topical sections on plenary lecture and tutorial papers; foundations of rough set theory; granular computing and covering-based rough sets; applications of rough sets; induction of decision rules - theory and practice; knowledge discovery; spatial data analysis and spatial databases; information extraction from images.

Author : Hongfang Lu,Zhao-Dong Xu,Tom Iseley,Haoyan Peng,Lingdi Fu
Publisher : Springer Nature
Page : 295 pages
File Size : 51,6 Mb
Release : 2023-01-03
Category : Technology & Engineering
ISBN : 9789811967986

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Pipeline Inspection and Health Monitoring Technology by Hongfang Lu,Zhao-Dong Xu,Tom Iseley,Haoyan Peng,Lingdi Fu Pdf

This book includes six chapters aiming to introduce global pipeline inspection and health monitoring technologies comprehensively. The pipeline is the blood vessel of the energy system and a vital lifeline project. After many years of service, the pipeline gradually enters the aging stage. Pipeline inspection and health monitoring can effectively reduce the failure and accident risks of the pipeline, and it is conducive to integrity management. Through case analysis, practitioners can have a deeper understanding of the application of related technologies.

Author : André Britto,Karina Valdivia Delgado
Publisher : Springer Nature
Page : 564 pages
File Size : 43,9 Mb
Release : 2021-11-27
Category : Computers
ISBN : 9783030917029

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Intelligent Systems by André Britto,Karina Valdivia Delgado Pdf

The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in São Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.

Author : C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publisher : Springer Nature
Page : 412 pages
File Size : 41,7 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9789811500947

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Big Data Analytics: Systems, Algorithms, Applications by C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston Pdf

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.