Machine Learning: Theory and Applications: Volume 31
Machine Learning: Theory and Applications
Published on 17. May 2013
Book
Hardback
552 pages
978-0-444-53859-8 (ISBN)
Description
Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.
More details
Series
Language
English
Place of publication
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Computer scientists, artificial intelligence researchers, biometricians, and statisticians
Product notice
Laminated cover
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 30 mm
Weight
901 gr
ISBN-13
978-0-444-53859-8 (9780444538598)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Handbook of Statistics
Machine Learning: Theory and Applications
E-Book
05/2014
North-Holland
€195.00
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C. Radhakrishna Rao | Venu Govindaraju
Handbook of Statistics: 31
Machine Learning: Theory and Applications
Book
07/2013
North-Holland
€230.27
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Persons
book "Ancient Inhabitants of Jebel Moya? published by the Cambridge Press under the joint authorship of Rao and two anthropologists. On the basis of work done at CU during the two year period, 1946-1948, Rao earned a Ph.D. degree and a few years later Sc.D. degree of CU and the rare honor of life fellowship of Kings College, Cambridge.
He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao's Orthogonal arrays used in quality control, Rao's score test, Rao's Quadratic Entropy used in ecological work, Rao's metric and distance which are incorporated in most statistical books.
He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.
He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.'s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.
Dr. Venu Govindaraju, SUNY Distinguished Professor of Computer Science and Engineering, is the Vice President of Research and Economic Development of the University at Buffalo and founding director of the Center for Unified Biometrics and Sensors. He received his Bachelor's degree with honors from the Indian Institute of Technology (IIT) in 1986, and his Ph.D. from UB in 1992. His research focus is on machine learning and pattern recognition in the domains of Document Image Analysis and Biometrics. Dr. Govindaraju has co-authored about 400 refereed scientific papers. His seminal work in handwriting recognition was at the core of the first handwritten address interpretation system used by the US Postal Service. He was also the prime technical lead responsible for technology transfer to the Postal Services in US, Australia, and UK. He has been a Principal or Co-Investigator of sponsored projects funded for about 65 million dollars. Dr. Govindaraju has supervised the dissertations of 30 doctoral students. He has served on the editorial boards of premier journals such as the IEEE Transactions on Pattern Analysis and Machine Intelligence and is currently the Editor-in-Chief of the IEEE Biometrics Council Compendium. Dr. Govindaraju is a Fellow of the ACM (Association of Computing Machinery), IEEE (Institute of Electrical and Electronics Engineers), AAAS (American Association for the Advancement of Science), the IAPR (International Association of Pattern Recognition), and the SPIE (International Society of Optics and Photonics). He is recipient of the 2004 MIT Global Indus Technovator award and the 2010 IEEE Technical Achievement award.
He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao's Orthogonal arrays used in quality control, Rao's score test, Rao's Quadratic Entropy used in ecological work, Rao's metric and distance which are incorporated in most statistical books.
He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.
He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.'s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.
Dr. Venu Govindaraju, SUNY Distinguished Professor of Computer Science and Engineering, is the Vice President of Research and Economic Development of the University at Buffalo and founding director of the Center for Unified Biometrics and Sensors. He received his Bachelor's degree with honors from the Indian Institute of Technology (IIT) in 1986, and his Ph.D. from UB in 1992. His research focus is on machine learning and pattern recognition in the domains of Document Image Analysis and Biometrics. Dr. Govindaraju has co-authored about 400 refereed scientific papers. His seminal work in handwriting recognition was at the core of the first handwritten address interpretation system used by the US Postal Service. He was also the prime technical lead responsible for technology transfer to the Postal Services in US, Australia, and UK. He has been a Principal or Co-Investigator of sponsored projects funded for about 65 million dollars. Dr. Govindaraju has supervised the dissertations of 30 doctoral students. He has served on the editorial boards of premier journals such as the IEEE Transactions on Pattern Analysis and Machine Intelligence and is currently the Editor-in-Chief of the IEEE Biometrics Council Compendium. Dr. Govindaraju is a Fellow of the ACM (Association of Computing Machinery), IEEE (Institute of Electrical and Electronics Engineers), AAAS (American Association for the Advancement of Science), the IAPR (International Association of Pattern Recognition), and the SPIE (International Society of Optics and Photonics). He is recipient of the 2004 MIT Global Indus Technovator award and the 2010 IEEE Technical Achievement award.
Content
1. The Sequential Bootstrap2. The Cross-Entropy Method for Estimation3. The Cross-Entropy Method for Optimization4. Probability Collectives in Optimization5. Bagging, Boosting, and Random Forests Using R6. Matching Score Fusion Methods7. Statistical Methods on Special Manifolds for Image and Video Understanding8. Dictionary-based Methods for Object Recognition9. Conditional Random Fields for Scene Labeling10. Shape Based Image Classification and Retrieval11. Visual Search: A Large-Scale Perspective12. Video Activity Recognition by Luminance Differential Trajectory and Aligned Projection Distance13. Soft Biometrics for Surveillance: An Overview14. A User Behavior Monitoring and Profiling Scheme for Masquerade Detection 15. Application of Bayesian Graphical Models to Iris Recognition16. Learning Algorithms for Document Layout Analysis17. Hidden Markov Models for Off-Line Cursive Handwriting Recognition18. Machine Learning in Handwritten Arabic Text Recognition19. Manifold learning for the shape-based recognition of historical Arabic documents20. Query Suggestion with Large Scale Data