Download or read book Statistical and Inductive Inference by Minimum Message Length written by C.S. Wallace and published by Springer Science & Business Media. This book was released on 2005-05-26 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the ‘best’ explanation of observed data is the shortest. Further, an explanation is acceptable (i.e. the induction is justified) only if the explanation is shorter than the original data. This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science. Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining. C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focused primarily on the Minimum Message Length Principle.
Download or read book Information Statistics and Induction in Science written by David L. Dowe and published by World Scientific. This book was released on 1996 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Coding Ockham s Razor written by Lloyd Allison and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores inductive inference using the minimum message length (MML) principle, a Bayesian method which is a realisation of Ockham's Razor based on information theory. Accompanied by a library of software, the book can assist an applications programmer, student or researcher in the fields of data analysis and machine learning to write computer programs based upon this principle. MML inference has been around for 50 years and yet only one highly technical book has been written about the subject. The majority of research in the field has been backed by specialised one-off programs but this book includes a library of general MML-based software, in Java. The Java source code is available under the GNU GPL open-source license. The software library is documented using Javadoc which produces extensive cross referenced HTML manual pages. Every probability distribution and statistical model that is described in the book is implemented and documented in the software library. The library may contain a component that directly solves a reader's inference problem, or contain components that can be put together to solve the problem, or provide a standard interface under which a new component can be written to solve the problem. This book will be of interest to application developers in the fields of machine learning and statistics as well as academics, postdocs, programmers and data scientists. It could also be used by third year or fourth year undergraduate or postgraduate students.
Download or read book The Minimum Description Length Principle written by Peter D. Grünwald and published by MIT Press. This book was released on 2007 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the MDL Principle provides a reference accessible to graduate students and researchers in statistics, pattern classification, machine learning, and data mining, to philosophers interested in the foundations of statistics, and to researchers in other applied sciences that involve model selection.
Download or read book Information Theoretic Learning written by Jose C. Principe and published by Springer Science & Business Media. This book was released on 2010-04-06 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.
Download or read book Advances in Minimum Description Length written by Peter D. Grünwald and published by MIT Press. This book was released on 2005 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: A source book for state-of-the-art MDL, including an extensive tutorial and recent theoretical advances and practical applications in fields ranging from bioinformatics to psychology.
Download or read book Algorithmic Probability and Friends Bayesian Prediction and Artificial Intelligence written by David L. Dowe and published by Springer. This book was released on 2013-10-22 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic probability and friends: Proceedings of the Ray Solomonoff 85th memorial conference is a collection of original work and surveys. The Solomonoff 85th memorial conference was held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff (1926-2009), honouring his various pioneering works - most particularly, his revolutionary insight in the early 1960s that the universality of Universal Turing Machines (UTMs) could be used for universal Bayesian prediction and artificial intelligence (machine learning). This work continues to increasingly influence and under-pin statistics, econometrics, machine learning, data mining, inductive inference, search algorithms, data compression, theories of (general) intelligence and philosophy of science - and applications of these areas. Ray not only envisioned this as the path to genuine artificial intelligence, but also, still in the 1960s, anticipated stages of progress in machine intelligence which would ultimately lead to machines surpassing human intelligence. Ray warned of the need to anticipate and discuss the potential consequences - and dangers - sooner rather than later. Possibly foremostly, Ray Solomonoff was a fine, happy, frugal and adventurous human being of gentle resolve who managed to fund himself while electing to conduct so much of his paradigm-changing research outside of the university system. The volume contains 35 papers pertaining to the abovementioned topics in tribute to Ray Solomonoff and his legacy.
Download or read book AI 2005 Advances in Artificial Intelligence written by Shichao Zhang and published by Springer Science & Business Media. This book was released on 2005-11-21 with total page 1369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th Australian Joint Conference on Artificial Intelligence, AI 2005, held in Sydney, Australia in December 2005. The 77 revised full papers and 119 revised short papers presented together with the abstracts of 3 keynote speeches were carefully reviewed and selected from 535 submissions. The papers are catgorized in three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. Particular topics addressed by the papers are logic and reasoning, machine learning, game theory, robotic technology, data mining, neural networks, fuzzy theory and algorithms, evolutionary computing, Web intelligence, decision making, pattern recognition, agent technology, and AI applications.
Download or read book AI 2010 Advances in Artificial Intelligence written by Jiuyong Li and published by Springer. This book was released on 2010-11-23 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence, AI 2010, held in Adelaide, Australia, in December 2010. The 52 revised full papers presented were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on knowledge representation and reasoning; data mining and knowledge discovery; machine learning; statistical learning; evolutionary computation; particle swarm optimization; intelligent agent; search and planning; natural language processing; and AI applications.
Download or read book Advances in Computing and Information ICCI 90 written by Selim G. Akl and published by Springer Science & Business Media. This book was released on 1990 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains selected and invited papers presented at the International Conference on Computing and Information, ICCI '90, Niagara Falls, Ontario, Canada, May 23-26, 1990. ICCI conferences provide an international forum for presenting new results in research, development and applications in computing and information. Their primary goal is to promote an interchange of ideas and cooperation between practitioners and theorists in the interdisciplinary fields of computing, communication and information theory. The four main topic areas of ICCI '90 are: - Information and coding theory, statistics and probability, - Foundations of computer science, theory of algorithms and programming, - Concurrency, parallelism, communications, networking, computer architecture and VLSI, - Data and software engineering, databases, expert systems, information systems, decision making, and AI methodologies.
Download or read book MICAI 2006 Advances in Artificial Intelligence written by Alexander Gelbukh and published by Springer Science & Business Media. This book was released on 2006-11-07 with total page 1258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Mexican International Conference on Artificial Intelligence, MICAI 2006, held in Apizaco, Mexico in November 2006. It contains over 120 papers that address such topics as knowledge representation and reasoning, machine learning and feature selection, knowledge discovery, computer vision, image processing and image retrieval, robotics, as well as bioinformatics and medical applications.
Download or read book AI 2009 Advances in Artificial Intelligence written by Ann Nicholson and published by Springer. This book was released on 2009-11-18 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence, AI 2009, held in Melbourne, Australia, in December 2009. The 68 revised full papers presented were carefully reviewed and selected from 174 submissions. The papers are organized in topical sections on agents; AI applications; computer vision and image processing; data mining and statistical learning; evolutionary computing; game playing; knowledge representation and reasoning; natural language and speech processing; soft computing; and user modelling.
Download or read book AI 2016 Advances in Artificial Intelligence written by Byeong Ho Kang and published by Springer. This book was released on 2016-11-25 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 29th Australasian Joint Conference on Artificial Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016. The 40 full papers and 18 short papers presented together with 8 invited short papers were carefully reviewed and selected from 121 submissions. The papers are organized in topical sections on agents and multiagent systems; AI applications and innovations; big data; constraint satisfaction, search and optimisation; knowledge representation and reasoning; machine learning and data mining; social intelligence; and text mining and NLP. The proceedings also contains 2 contributions of the AI 2016 doctoral consortium and 6 contributions of the SMA 2016.
Download or read book Learning with the Minimum Description Length Principle written by Kenji Yamanishi and published by Springer Nature. This book was released on 2023-10-16 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to the minimum description length (MDL) principle and its applications in learning. The MDL is a fundamental principle for inductive inference, which is used in many applications including statistical modeling, pattern recognition and machine learning. At its core, the MDL is based on the premise that “the shortest code length leads to the best strategy for learning anything from data.” The MDL provides a broad and unifying view of statistical inferences such as estimation, prediction and testing and, of course, machine learning. The content covers the theoretical foundations of the MDL and broad practical areas such as detecting changes and anomalies, problems involving latent variable models, and high dimensional statistical inference, among others. The book offers an easy-to-follow guide to the MDL principle, together with other information criteria, explaining the differences between their standpoints. Written in a systematic, concise and comprehensive style, this book is suitable for researchers and graduate students of machine learning, statistics, information theory and computer science.
Download or read book AI 2013 Advances in Artificial Intelligence written by Stephen Cranefield and published by Springer. This book was released on 2013-11-08 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 26th Australasian Joint Conference on Artificial Intelligence, AI 2013, held in Dunedin, New Zealand, in December 2013. The 35 revised full papers and 19 revised short papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections as agents; AI applications; cognitive modelling; computer vision; constraint satisfaction, search and optimisation; evolutionary computation; game playing; knowledge representation and reasoning; machine learning and data mining; natural language processing and information retrieval; planning and scheduling.
Download or read book AI 2012 Advances in Artificial Intelligence written by Michael Thielscher and published by Springer. This book was released on 2013-02-01 with total page 935 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 25th Australasian Joint Conference on Artificial Intelligence, AI 2012, held in Sydney, Australia, in December 2012. The 76 revised full papers presented were carefully reviewed and selected from 196 submissions. The papers address a wide range of agents, applications, computer vision, constraints and search, game playing, information retrieval, knowledge representation, machine learning, planning and scheduling, robotics and uncertainty in AI.
Download or read book Coding Ockham s Razor written by Lloyd Allison and published by Springer. This book was released on 2018-05-04 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores inductive inference using the minimum message length (MML) principle, a Bayesian method which is a realisation of Ockham's Razor based on information theory. Accompanied by a library of software, the book can assist an applications programmer, student or researcher in the fields of data analysis and machine learning to write computer programs based upon this principle. MML inference has been around for 50 years and yet only one highly technical book has been written about the subject. The majority of research in the field has been backed by specialised one-off programs but this book includes a library of general MML–based software, in Java. The Java source code is available under the GNU GPL open-source license. The software library is documented using Javadoc which produces extensive cross referenced HTML manual pages. Every probability distribution and statistical model that is described in the book is implemented and documented in the software library. The library may contain a component that directly solves a reader's inference problem, or contain components that can be put together to solve the problem, or provide a standard interface under which a new component can be written to solve the problem. This book will be of interest to application developers in the fields of machine learning and statistics as well as academics, postdocs, programmers and data scientists. It could also be used by third year or fourth year undergraduate or postgraduate students.
