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Subspace Latent Structure And Feature Selection
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Book Synopsis Subspace, Latent Structure and Feature Selection by : Craig Saunders
Download or read book Subspace, Latent Structure and Feature Selection written by Craig Saunders and published by Springer. This book was released on 2006-05-24 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005. The 9 revised full papers presented together with 5 invited papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, among others.
Book Synopsis Subspace, Latent Structure and Feature Selection by : Craig Saunders
Download or read book Subspace, Latent Structure and Feature Selection written by Craig Saunders and published by Springer. This book was released on 2006-05-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005. The 9 revised full papers presented together with 5 invited papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, among others.
Book Synopsis Subspace, Latent Structure and Feature Selection by : Craig Saunders
Download or read book Subspace, Latent Structure and Feature Selection written by Craig Saunders and published by Springer Science & Business Media. This book was released on 2006-05-16 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many of the papers in this proceedings volume were presented at the PASCAL Workshop entitled Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimization Perspectives which took place in Bohinj, Slovenia during February, 23–25 2005.
Book Synopsis Subspace, Latent Structure and Feature Selection by :
Download or read book Subspace, Latent Structure and Feature Selection written by and published by . This book was released on 2006 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition by : Joachim Denzler
Download or read book Pattern Recognition written by Joachim Denzler and published by Springer. This book was released on 2009-09-02 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 31st Symposium of the German Association for Pattern Recognition, DAGM 2009, held in Jena, Germany, in September 2009. The 56 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on motion and tracking; pedestrian recognition and automotive applications; features; single-view and 3D reconstruction; learning and classification; pattern recognition and estimation; stereo and multi-view reconstruction; image analysis and applications; and segmentation.
Book Synopsis 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007) by : Steffen Leonhardt
Download or read book 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007) written by Steffen Leonhardt and published by Springer Science & Business Media. This book was released on 2007-05-04 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers from the International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2007, held in March 2007 at the University Hospital Aachen, Germany. Topics covered in the volume include new medical measurements, smart bio-sensing textiles, low-power wireless networking, system integration, medical signal processing, multi-sensor data fusion, and on-going standardization activities.
Book Synopsis Handbook of Statistical Bioinformatics by : Henry Horng-Shing Lu
Download or read book Handbook of Statistical Bioinformatics written by Henry Horng-Shing Lu and published by Springer Science & Business Media. This book was released on 2011-05-17 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Book Synopsis Advances in Intelligent Decision Technologies by : Gloria Phillips-Wren
Download or read book Advances in Intelligent Decision Technologies written by Gloria Phillips-Wren and published by Springer Science & Business Media. This book was released on 2010-07-19 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Decision Technologies (IDT) seeks an interchange of research on intelligent systems and intelligent technologies which enhance or improve decision making in industry, government and academia. The focus is interdisciplinary in nature, and includes research on all aspects of intelligent decision technologies, from fundamental development to the applied system. This volume represents leading research from the Second KES International Symposium on Intelligent Decision Technologies (KES IDT’10), hosted and organized by the Sellinger School of Business and Management, Loyola University Maryland, USA, in conjunction with KES International. The symposium was concerned with theory, design development, implementation, testing and evaluation of intelligent decision systems. Topics include decision making theory, intelligent agents, fuzzy logic, multi-agent systems, Bayesian networks, optimization, artificial neural networks, genetic algorithms, expert systems, decision support systems, geographic information systems, case-based reasoning, time series, knowledge management systems, Kansei communication, rough sets, spatial decision analysis, and multi-criteria decision analysis. These technologies have the potential to revolutionize decision making in many areas of management, healthcare, international business, finance, accounting, marketing, military applications, ecommerce, network management, crisis response, building design, information retrieval, and disaster recovery.
Book Synopsis Learning to Understand Remote Sensing Images by : Qi Wang
Download or read book Learning to Understand Remote Sensing Images written by Qi Wang and published by MDPI. This book was released on 2019-09-30 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Book Synopsis Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques by : Lodhi, Huma
Download or read book Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques written by Lodhi, Huma and published by IGI Global. This book was released on 2010-07-31 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.
Book Synopsis Big Data Analytics in Chemoinformatics and Bioinformatics by : Subhash C. Basak
Download or read book Big Data Analytics in Chemoinformatics and Bioinformatics written by Subhash C. Basak and published by Elsevier. This book was released on 2022-12-06 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry
Book Synopsis Web Information Systems - WISE 2006 Workshops by : Ling Feng
Download or read book Web Information Systems - WISE 2006 Workshops written by Ling Feng and published by Springer Science & Business Media. This book was released on 2006-10-11 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the three workshops held in conjunction with the 7th International Conference on Web Information Systems, WISE 2006, in Wuhan, China, in October 2006.
Book Synopsis Emerging Sensor Technology in Agriculture by : Sigfredo Fuentes
Download or read book Emerging Sensor Technology in Agriculture written by Sigfredo Fuentes and published by MDPI. This book was released on 2020-11-25 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of research. The diversity of applications in which digital agriculture can make an important difference in day-to-day farming decision making makes this discipline an important focus of research internationally.
Book Synopsis Multivariate Biomarker Discovery by : Darius M. Dziuda
Download or read book Multivariate Biomarker Discovery written by Darius M. Dziuda and published by Cambridge University Press. This book was released on 2024-05-31 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise guide to all aspects of predictive modeling for biomarker discovery for medical diagnosis, prognosis, and personalized medicine.
Book Synopsis Handbook of Digital Forensics of Multimedia Data and Devices, Enhanced E-Book by : Anthony T. S. Ho
Download or read book Handbook of Digital Forensics of Multimedia Data and Devices, Enhanced E-Book written by Anthony T. S. Ho and published by John Wiley & Sons. This book was released on 2016-05-20 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital forensics and multimedia forensics are rapidly growing disciplines whereby electronic information is extracted and interpreted for use in a court of law. These two fields are finding increasing importance in law enforcement and the investigation of cybercrime as the ubiquity of personal computing and the internet becomes ever-more apparent. Digital forensics involves investigating computer systems and digital artefacts in general, while multimedia forensics is a sub-topic of digital forensics focusing on evidence extracted from both normal computer systems and special multimedia devices, such as digital cameras. This book focuses on the interface between digital forensics and multimedia forensics, bringing two closely related fields of forensic expertise together to identify and understand the current state-of-the-art in digital forensic investigation. Both fields are expertly attended to by contributions from researchers and forensic practitioners specializing in diverse topics such as forensic authentication, forensic triage, forensic photogrammetry, biometric forensics, multimedia device identification, and image forgery detection among many others. Key features: Brings digital and multimedia forensics together with contributions from academia, law enforcement, and the digital forensics industry for extensive coverage of all the major aspects of digital forensics of multimedia data and devices Provides comprehensive and authoritative coverage of digital forensics of multimedia data and devices Offers not only explanations of techniques but also real-world and simulated case studies to illustrate how digital and multimedia forensics techniques work Includes a companion website hosting continually updated supplementary materials ranging from extended and updated coverage of standards to best practice guides, test datasets and more case studies
Book Synopsis Digital Signal Processing with Kernel Methods by : Jose Luis Rojo-Alvarez
Download or read book Digital Signal Processing with Kernel Methods written by Jose Luis Rojo-Alvarez and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
Download or read book Boosting written by Robert E. Schapire and published by MIT Press. This book was released on 2014-01-10 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
