Artificial Intelligence
- 1st Edition, Volume 49 - August 25, 2023
- Editors: Arni S.R. Srinivasa Rao, C.R. Rao, Steven Krantz
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 3 - 1 3 7 6 3 - 1
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 3 7 6 4 - 8
Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of… Read more
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Request a sales quoteArtificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more.
Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics.
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Handbook of Statistics series
- Includes the latest information on Artificial Intelligence
- Cover image
- Title page
- Table of Contents
- Series Page
- Copyright
- Contributors
- Preface
- Part I: Foundations and methods
- Chapter 1: Object-oriented basis of artificial intelligence methodologies
- Abstract
- 1: OO in AI
- 2: Business requirements to ML problem formulation
- 3: ML tools and implementation
- 4: ML Performance monitoring
- 5: Scope and limitation of the ML formulation
- 6: Is the human brain the same as an artificial neural network?
- 7: Summary of the chapter
- 8: Review questions
- Acknowledgement
- References
- Chapter 2: Machine learning in physics and geometry
- Abstract
- 1: Introduction and summary
- 2: Background physics and mathematics
- 3: Supervised learning
- 4: Unsupervised learning
- 5: Conclusion
- References
- Part II: Probability inspired models
- Chapter 3: Learning and identity testing of Markov chains
- Abstract
- 1: Introduction
- 2: Preliminaries
- 3: Estimation of transition matrix
- 4: Identity testing of transition matrix
- 5: Concluding remarks
- References
- Chapter 4: Data privacy for machine learning and statistics
- Abstract
- 1: Introduction
- 2: Disclosure risk and privacy models
- 3: Some protection mechanisms
- 4: Conclusions and future research
- References
- Chapter 5: A Teacher–Student-based adaptive structural deep learning model and its estimating uncertainty of image data
- Abstract
- 1: Introduction
- 2: Adaptive structural learning method of DBN
- 3: Teacher–Student-based Adaptive DBN
- 4: Adaptive DBN model for ADNI data set
- 5: Conclusive discussion
- References
- Part III: Applications
- Chapter 6: Artificial intelligence in systems biology
- Abstract
- 1: Introduction
- 2: High-throughput imbalance multi-omics data
- 3: Complex hierarchical biological networks
- 4: Drug discovery
- 5: Structural systems biology
- 6: Conclusion
- References
- Chapter 7: The calculated uncertainty of scientific discovery: From Maths to Deep Maths
- Abstract
- 1: Introduction
- 2: An abridged history of mathematics and philosophy in science
- 3: The expanding computational universe (Fig. 1)
- 4: The machine discovery era (present–future)
- References
- Chapter 8: Indian courts of law can benefit immensely by adopting artificial intelligence methods in bail applications for speedy and accurate justice
- Abstract
- 1: Introduction
- 2: Deep learning of law rules
- 3: Theory and method of implementation
- 4: The role of data and statistics
- 5: Conclusions
- Acknowledgments
- References
- Further reading
- Index
- No. of pages: 420
- Language: English
- Edition: 1
- Volume: 49
- Published: August 25, 2023
- Imprint: Academic Press
- Hardback ISBN: 9780443137631
- eBook ISBN: 9780443137648
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Arni S.R. Srinivasa Rao
Arni S.R. Srinivasa Rao works in pure mathematics, applied mathematics, probability, and artificial intelligence and applications in medicine. He is a Professor at the Medical College of Georgia, Augusta University, U.S.A, and the Director of the Laboratory for Theory and Mathematical Modeling housed within the Division of Infectious Diseases, Medical College of Georgia, Augusta, U.S.A. Previously, Dr. Rao conducted research and/or taught at Mathematical Institute, University of Oxford (2003, 2005-07), Indian Statistical Institute (1998-2002, 2006-2012), Indian Institute of Science (2002-04), University of Guelph (2004-06). Until 2012, Dr. Rao held a permanent faculty position at the Indian Statistical Institute. He has won the Heiwa-Nakajima Award (Japan) and Fast Track Young Scientists Fellowship in Mathematical Sciences (DST, New Delhi). Dr. Rao also proved a major theorem in stationary population models, such as, Rao's Partition Theorem in Populations, Rao-Carey Theorem in stationary populations, and developed mathematical modeling-based policies for the spread of diseases like HIV, H5N1, COVID-19, etc. He developed a new set of network models for understanding avian pathogen biology on grid graphs (these were called chicken walk models), AI Models for COVID-19 and received wide coverage in the science media. Recently, he developed concepts such as “Exact Deep Learning Machines”, and “Multilevel Contours” within a bundle of Complex Number Planes.
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C.R. Rao
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.
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