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 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.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Series Page - p. iii 5. Copyright - p. iii 6. Contributors - p. iii 7. Preface - p. xiii 8. Part I - p. xv 9. Part I: Foundations and methods - p. xv 10. Chapter 1: Object-oriented basis of artificial intelligence methodologies - p. 25 11. Chapter 2: Machine learning in physics and geometry - p. 47 12. Part II - p. 81 13. Part II: Probability inspired models - p. 81 14. Chapter 3: Learning and identity testing of Markov chains - p. 85 15. Chapter 4: Data privacy for machine learning and statistics - p. 103 16. Chapter 5: A Teacher–Student-based adaptive structural deep learning model and its estimating uncertainty of image data - p. 129 17. Part III - p. 149 18. Part III: Applications - p. 149 19. Chapter 6: Artificial intelligence in systems biology - p. 153 20. Chapter 7: The calculated uncertainty of scientific discovery: From Maths to Deep Maths - p. 205 21. Chapter 8: Indian courts of law can benefit immensely by adopting artificial intelligence methods in bail applications for speedy and accurate justice - p. 227 22. Index - p. 236
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 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.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Series Page - p. iii 5. Copyright - p. iii 6. Contributors - p. iii 7. Preface - p. xiii 8. Part I - p. xv 9. Part I: Foundations and methods - p. xv 10. Chapter 1: Object-oriented basis of artificial intelligence methodologies - p. 25 11. Chapter 2: Machine learning in physics and geometry - p. 47 12. Part II - p. 81 13. Part II: Probability inspired models - p. 81 14. Chapter 3: Learning and identity testing of Markov chains - p. 85 15. Chapter 4: Data privacy for machine learning and statistics - p. 103 16. Chapter 5: A Teacher–Student-based adaptive structural deep learning model and its estimating uncertainty of image data - p. 129 17. Part III - p. 149 18. Part III: Applications - p. 149 19. Chapter 6: Artificial intelligence in systems biology - p. 153 20. Chapter 7: The calculated uncertainty of scientific discovery: From Maths to Deep Maths - p. 205 21. Chapter 8: Indian courts of law can benefit immensely by adopting artificial intelligence methods in bail applications for speedy and accurate justice - p. 227 22. Index - p. 236
