Advances In Large Margin Classifiers
DOWNLOAD
Download Advances In Large Margin Classifiers PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Advances In Large Margin Classifiers book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Advances In Large Margin Classifiers
DOWNLOAD
Author : Alexander J. Smola
language : en
Publisher: MIT Press
Release Date : 2000
Advances In Large Margin Classifiers written by Alexander J. Smola and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
Advances In Large Margin Classifiers
DOWNLOAD
Author : Alexander J. Smola
language : en
Publisher: Bradford Books
Release Date : 2000
Advances In Large Margin Classifiers written by Alexander J. Smola and has been published by Bradford Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
Advances In Neural Information Processing Systems 19
DOWNLOAD
Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2007
Advances In Neural Information Processing Systems 19 written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Artificial intelligence categories.
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
Advanced Lectures On Machine Learning
DOWNLOAD
Author : Shahar Mendelson
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-01-31
Advanced Lectures On Machine Learning written by Shahar Mendelson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-31 with Computers categories.
This book presents revised reviewed versions of lectures given during the Machine Learning Summer School held in Canberra, Australia, in February 2002. The lectures address the following key topics in algorithmic learning: statistical learning theory, kernel methods, boosting, reinforcement learning, theory learning, association rule learning, and learning linear classifier systems. Thus, the book is well balanced between classical topics and new approaches in machine learning. Advanced students and lecturers will find this book a coherent in-depth overview of this exciting area, while researchers will use this book as a valuable source of reference.
Learning With Kernels
DOWNLOAD
Author : Bernhard Scholkopf
language : en
Publisher: MIT Press
Release Date : 2018-06-05
Learning With Kernels written by Bernhard Scholkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-05 with Computers categories.
A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.
Advances Of Computational Intelligence In Industrial Systems
DOWNLOAD
Author : Ying Liu
language : en
Publisher: Springer
Release Date : 2008-05-30
Advances Of Computational Intelligence In Industrial Systems written by Ying Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-30 with Computers categories.
Computational Intelligence (CI) has emerged as a rapid growing field over the past decade. Its various techniques have been recognized as powerful tools for intelligent information processing, decision making and knowledge management. "Advances of Computational Intelligence in Industrial Systems" reports the exploration of CI frontiers with an emphasis on a broad spectrum of real-world applications. Section I – Theory and Foundation presents some of the latest developments in CI, e.g. particle swarm optimization, Web services, data mining with privacy protection, kernel methods for text analysis, etc. Section II – Industrial Application covers the CI applications in a wide variety of domains, e.g. clinical decision support, process monitoring for industrial CNC machine, novelty detection for jet engines, ant algorithm for berth allocation, etc. Such a collection of chapters has presented the state-of-the-art of CI applications in industry and will be an essential resource for professionals and researchers who wish to learn and spot the opportunities in applying CI techniques to their particular problems.
Advances In Knowledge Discovery And Data Mining
DOWNLOAD
Author : James Bailey
language : en
Publisher: Springer
Release Date : 2016-04-11
Advances In Knowledge Discovery And Data Mining written by James Bailey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-11 with Computers categories.
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.
Micai 2005 Advances In Artificial Intelligence
DOWNLOAD
Author : Alexander Gelbukh
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-11-04
Micai 2005 Advances In Artificial Intelligence written by Alexander Gelbukh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-04 with Computers categories.
This book constitutes the refereed proceedings of the 4th Mexican International Conference on Artificial Intelligence, MICAI 2005, held in Monterrey, Mexico, in November 2005. The 120 revised full papers presented were carefully reviewed and selected from 423 submissions. The papers are organized in topical sections on knowledge representation and management, logic and constraint programming, uncertainty reasoning, multiagent systems and distributed AI, computer vision and pattern recognition, machine learning and data mining, evolutionary computation and genetic algorithms, neural networks, natural language processing, intelligent interfaces and speech processing, bioinformatics and medical applications, robotics, modeling and intelligent control, and intelligent tutoring systems.
Performance Modeling And Engineering
DOWNLOAD
Author : Zhen Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-12
Performance Modeling And Engineering written by Zhen Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-12 with Computers categories.
With the fast development of networking and software technologies, information processing infrastructure and applications have been growing at an impressive rate in both size and complexity, to such a degree that the design and development of high performance and scalable data processing systems and networks have become an ever-challenging issue. As a result, the use of performance modeling and m- surementtechniquesas a critical step in designand developmenthas becomea c- mon practice. Research and developmenton methodologyand tools of performance modeling and performance engineering have gained further importance in order to improve the performance and scalability of these systems. Since the seminal work of A. K. Erlang almost a century ago on the mod- ing of telephone traf c, performance modeling and measurement have grown into a discipline and have been evolving both in their methodologies and in the areas in which they are applied. It is noteworthy that various mathematical techniques were brought into this eld, including in particular probability theory, stochastic processes, statistics, complex analysis, stochastic calculus, stochastic comparison, optimization, control theory, machine learning and information theory. The app- cation areas extended from telephone networks to Internet and Web applications, from computer systems to computer software, from manufacturing systems to s- ply chain, from call centers to workforce management.