Algorithmic Learning In A Random World

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Algorithmic Learning in a Random World

Author : Vladimir Vovk
Publisher : Springer Science & Business Media
ISBN 13 : 9780387001524
Total Pages : 344 pages
Book Rating : 4.0/5 (15 download)

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Book Synopsis Algorithmic Learning in a Random World by : Vladimir Vovk

Download or read book Algorithmic Learning in a Random World written by Vladimir Vovk and published by Springer Science & Business Media. This book was released on 2005-03-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.

Algorithmic Learning in a Random World

Author : Vladimir Vovk
Publisher :
ISBN 13 : 9789780387259
Total Pages : 324 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Algorithmic Learning in a Random World by : Vladimir Vovk

Download or read book Algorithmic Learning in a Random World written by Vladimir Vovk and published by . This book was released on 2005 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Algorithms For Big Data

Author : Moran Feldman
Publisher : World Scientific
ISBN 13 : 9811204756
Total Pages : 458 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Algorithms For Big Data by : Moran Feldman

Download or read book Algorithms For Big Data written by Moran Feldman and published by World Scientific. This book was released on 2020-07-13 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.

Algorithmic Learning Theory

Author : Marcus Hutter
Publisher : Springer
ISBN 13 : 3642161081
Total Pages : 421 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Algorithmic Learning Theory by : Marcus Hutter

Download or read book Algorithmic Learning Theory written by Marcus Hutter and published by Springer. This book was released on 2010-09-02 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th - ternational Conference on Discovery Science (DS 2010) and with the Machine Learning Summer School, which was held just before ALT 2010. The tech- cal program of ALT 2010, contained 26 papers selected from 44 submissions and ?ve invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2010 was dedicated to the theoretical foundations of machine learning and took place on the campus of the Australian National University, Canberra, Australia. ALT provides a forum for high-quality talks with a strong theore- cal background and scienti?c interchange in areas such as inductive inference, universal prediction, teaching models, grammatical inference, formal languages, inductive logic programming, query learning, complexity of learning, on-line learning and relative loss bounds, semi-supervised and unsupervised learning, clustering,activelearning,statisticallearning,supportvectormachines,Vapnik- Chervonenkisdimension,probablyapproximatelycorrectlearning,Bayesianand causal networks, boosting and bagging, information-based methods, minimum descriptionlength,Kolmogorovcomplexity,kernels,graphlearning,decisiontree methods, Markov decision processes, reinforcement learning, and real-world - plications of algorithmic learning theory. DS 2010 was the 13th International Conference on Discovery Science and focused on the development and analysis of methods for intelligent data an- ysis, knowledge discovery and machine learning, as well as their application to scienti?c knowledge discovery. As is the tradition, it was co-located and held in parallel with Algorithmic Learning Theory.

Algorithmic Learning Theory

Author : Peter Auer
Publisher : Springer
ISBN 13 : 3319116622
Total Pages : 367 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Algorithmic Learning Theory by : Peter Auer

Download or read book Algorithmic Learning Theory written by Peter Auer and published by Springer. This book was released on 2014-10-01 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 25th International Conference on Algorithmic Learning Theory, ALT 2014, held in Bled, Slovenia, in October 2014, and co-located with the 17th International Conference on Discovery Science, DS 2014. The 21 papers presented in this volume were carefully reviewed and selected from 50 submissions. In addition the book contains 4 full papers summarizing the invited talks. The papers are organized in topical sections named: inductive inference; exact learning from queries; reinforcement learning; online learning and learning with bandit information; statistical learning theory; privacy, clustering, MDL, and Kolmogorov complexity.

Conformal Prediction for Reliable Machine Learning

Author : Vineeth Balasubramanian
Publisher : Newnes
ISBN 13 : 0124017150
Total Pages : 323 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Conformal Prediction for Reliable Machine Learning by : Vineeth Balasubramanian

Download or read book Conformal Prediction for Reliable Machine Learning written by Vineeth Balasubramanian and published by Newnes. This book was released on 2014-04-23 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection

The Master Algorithm

Author : Pedro Domingos
Publisher : Basic Books
ISBN 13 : 0465061923
Total Pages : 354 pages
Book Rating : 4.4/5 (65 download)

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Book Synopsis The Master Algorithm by : Pedro Domingos

Download or read book The Master Algorithm written by Pedro Domingos and published by Basic Books. This book was released on 2015-09-22 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

Algorithmic Learning Theory

Author : Yoav Freund
Publisher : Springer Science & Business Media
ISBN 13 : 3540879862
Total Pages : 480 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Algorithmic Learning Theory by : Yoav Freund

Download or read book Algorithmic Learning Theory written by Yoav Freund and published by Springer Science & Business Media. This book was released on 2008-09-29 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Algorithmic Learning Theory, ALT 2008, held in Budapest, Hungary, in October 2008, co-located with the 11th International Conference on Discovery Science, DS 2008. The 31 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 46 submissions. The papers are dedicated to the theoretical foundations of machine learning; they address topics such as statistical learning; probability and stochastic processes; boosting and experts; active and query learning; and inductive inference.

The Ethical Algorithm

Author : Michael Kearns
Publisher : Oxford University Press
ISBN 13 : 0190948213
Total Pages : 288 pages
Book Rating : 4.1/5 (99 download)

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Book Synopsis The Ethical Algorithm by : Michael Kearns

Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press. This book was released on 2019-10-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.

Algorithmic Learning Theory

Author : Hiroki Arimura
Publisher : Springer
ISBN 13 : 3540409920
Total Pages : 348 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : Hiroki Arimura

Download or read book Algorithmic Learning Theory written by Hiroki Arimura and published by Springer. This book was released on 2003-06-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Algorithmic Learning Theory, ALT 2000, held in Sydney, Australia in December 2000. The 22 revised full papers presented together with three invited papers were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on statistical learning, inductive logic programming, inductive inference, complexity, neural networks and other paradigms, support vector machines.

Algorithmic Learning Theory

Author : Ricard Gavaldà
Publisher : Springer
ISBN 13 : 3540396241
Total Pages : 320 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Algorithmic Learning Theory by : Ricard Gavaldà

Download or read book Algorithmic Learning Theory written by Ricard Gavaldà and published by Springer. This book was released on 2003-10-02 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Algorithmic Learning Theory, ALT 2003, held in Sapporo, Japan in October 2003. The 19 revised full papers presented together with 2 invited papers and abstracts of 3 invited talks were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on inductive inference, learning and information extraction, learning with queries, learning with non-linear optimization, learning from random examples, and online prediction.

Algorithmic Learning

Author : Alan Hutchinson
Publisher : Oxford University Press, USA
ISBN 13 :
Total Pages : 472 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Algorithmic Learning by : Alan Hutchinson

Download or read book Algorithmic Learning written by Alan Hutchinson and published by Oxford University Press, USA. This book was released on 1994 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a rapidly changing field within artificial intelligence, as more algorithms are identified and a theory of which algorithm will suit which purpose emerges. Artificial Learning provides a comprehensive introduction to all aspects of the subject and will be both aninvaluable text for students and a reference for practitioners seeking an up-to-date review.

Algorithmic Learning Theory

Author : Sanjay Jain
Publisher : Springer Science & Business Media
ISBN 13 : 354029242X
Total Pages : 502 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Algorithmic Learning Theory by : Sanjay Jain

Download or read book Algorithmic Learning Theory written by Sanjay Jain and published by Springer Science & Business Media. This book was released on 2005-09-26 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005. The 30 revised full papers presented together with 5 invited papers and an introduction by the editors were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on kernel-based learning, bayesian and statistical models, PAC-learning, query-learning, inductive inference, language learning, learning and logic, learning from expert advice, online learning, defensive forecasting, and teaching.

Algorithmic Aspects of Machine Learning

Author : Ankur Moitra
Publisher : Cambridge University Press
ISBN 13 : 1107184584
Total Pages : 161 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Algorithmic Aspects of Machine Learning by : Ankur Moitra

Download or read book Algorithmic Aspects of Machine Learning written by Ankur Moitra and published by Cambridge University Press. This book was released on 2018-09-27 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces cutting-edge research on machine learning theory and practice, providing an accessible, modern algorithmic toolkit.

Algorithmic Learning Theory

Author : Sanjay Jain
Publisher : Springer
ISBN 13 : 3642409350
Total Pages : 413 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Algorithmic Learning Theory by : Sanjay Jain

Download or read book Algorithmic Learning Theory written by Sanjay Jain and published by Springer. This book was released on 2013-09-27 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALT 2013, held in Singapore in October 2013, and co-located with the 16th International Conference on Discovery Science, DS 2013. The 23 papers presented in this volume were carefully reviewed and selected from 39 submissions. In addition the book contains 3 full papers of invited talks. The papers are organized in topical sections named: online learning, inductive inference and grammatical inference, teaching and learning from queries, bandit theory, statistical learning theory, Bayesian/stochastic learning, and unsupervised/semi-supervised learning.

The Constitution of Algorithms

Author : Florian Jaton
Publisher : MIT Press
ISBN 13 : 0262542145
Total Pages : 401 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis The Constitution of Algorithms by : Florian Jaton

Download or read book The Constitution of Algorithms written by Florian Jaton and published by MIT Press. This book was released on 2021-04-27 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: A laboratory study that investigates how algorithms come into existence. Algorithms--often associated with the terms big data, machine learning, or artificial intelligence--underlie the technologies we use every day, and disputes over the consequences, actual or potential, of new algorithms arise regularly. In this book, Florian Jaton offers a new way to study computerized methods, providing an account of where algorithms come from and how they are constituted, investigating the practical activities by which algorithms are progressively assembled rather than what they may suggest or require once they are assembled.

Algorithmic Learning Theory

Author : José L. Balcázar
Publisher : Springer
ISBN 13 : 3540466509
Total Pages : 393 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Algorithmic Learning Theory by : José L. Balcázar

Download or read book Algorithmic Learning Theory written by José L. Balcázar and published by Springer. This book was released on 2006-10-05 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006. The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning.