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.
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Table of Contents
Part I Foundations and methods 1. Object-oriented basis of artificial intelligence methodologies Kalidas Yeturu 2. Machine learning in physics and geometry Yang-Hui He, Elli Heyes, and Edward Hirst Part II Probability inspired models3. Learning and identity testing of Markov chains Geoffrey Wolfer and Aryeh Kontorovich 4. Data privacy for machine learning and statistics Vicenc� Torra 5. A Teacher-Student-based adaptive structural deep learning model and its estimating uncertainty of image data Takumi Ichimura, Shin Kamada, Toshihide Harada, and Ken Inoue Part III: Applications 6. Artificial intelligence in systems biology Abhijit Dasgupta and Rajat K. De 7. The calculated uncertainty of scientific discovery: From Maths to Deep Maths D. Douglas Miller 8. Indian courts of law can benefit immensely by adopting artificial intelligence methods in bail applications for speedy and accurate justice Arni S.R. Srinivasa Rao and Anil P. Gore
