Advances In Large Margin Classifiers PDF Download
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Author | : Alexander J. Smola |
Publisher | : MIT Press |
Total Pages | : 436 |
Release | : 2000 |
Genre | : Computers |
ISBN | : 9780262194488 |
Download Advances in Large Margin Classifiers Book in PDF, ePub and Kindle
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.
Author | : Petroula Tsampouka |
Publisher | : |
Total Pages | : 156 |
Release | : 2007 |
Genre | : |
ISBN | : |
Download Perceptron-like Large Margin Classifiers Book in PDF, ePub and Kindle
Author | : Bernhard Schölkopf |
Publisher | : MIT Press |
Total Pages | : 1668 |
Release | : 2007 |
Genre | : Artificial intelligence |
ISBN | : 0262195682 |
Download Advances in Neural Information Processing Systems 19 Book in PDF, ePub and Kindle
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.
Author | : Shahar Mendelson |
Publisher | : Springer Science & Business Media |
Total Pages | : 267 |
Release | : 2003-01-31 |
Genre | : Computers |
ISBN | : 3540005293 |
Download Advanced Lectures on Machine Learning Book in PDF, ePub and Kindle
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.
Author | : Bernhard Scholkopf |
Publisher | : MIT Press |
Total Pages | : 645 |
Release | : 2018-06-05 |
Genre | : Computers |
ISBN | : 0262536579 |
Download Learning with Kernels Book in PDF, ePub and Kindle
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.
Author | : Alexander Gelbukh |
Publisher | : Springer |
Total Pages | : 1223 |
Release | : 2005-11-19 |
Genre | : Computers |
ISBN | : 3540316531 |
Download MICAI 2005: Advances in Artificial Intelligence Book in PDF, ePub and Kindle
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.
Author | : Ralf Herbrich |
Publisher | : MIT Press |
Total Pages | : 393 |
Release | : 2022-11-01 |
Genre | : Computers |
ISBN | : 0262546590 |
Download Learning Kernel Classifiers Book in PDF, ePub and Kindle
An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier—a limited, but well-established and comprehensively studied model—and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PAC-Bayesian theory, data-dependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
Author | : Chang Wen-jer |
Publisher | : World Scientific |
Total Pages | : 960 |
Release | : 2017-07-19 |
Genre | : Computers |
ISBN | : 9813220309 |
Download Computer Science and Artificial Intelligence Book in PDF, ePub and Kindle
Held in Guilin of China from August 13-14, 2016, the 2016 International Conference on Computer Science and Artificial Intelligence (CSAI2016) provides an excellent international platform for all invited speakers, authors and participants to share their results and establish research collaborations for future research. The conference enjoys a wide spread participation. It would not only serve as an academic forum, but also a good opportunity to establish business cooperation. CSAI2016 proceedings collects the most up-to-date, comprehensive, and worldwide state-of-art knowledge on computer science and artificial intelligence. After strict peer-review, the proceedings put together 117 articles based on originality, significance and clarity for the purpose of the conference.
Author | : Haruna Chiroma |
Publisher | : Springer Nature |
Total Pages | : 316 |
Release | : 2021-04-01 |
Genre | : Technology & Engineering |
ISBN | : 3030662888 |
Download Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics Book in PDF, ePub and Kindle
This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.
Author | : Sanjay Madria |
Publisher | : Springer Nature |
Total Pages | : 466 |
Release | : 2019-12-12 |
Genre | : Computers |
ISBN | : 3030371883 |
Download Big Data Analytics Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad, India, in December 2019. The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning.