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Independent component analysis : a tutorial introduction
"A Bradford book."Independent component analysis (ICA) is becoming an increasingly important tool for analyzing large data sets. In essence, ICA separates an observed set of signal mixtures into a set of statistically independent component signals, or source signals. In so doing, this powerful method can extract the relatively small amount of useful information typically found in large data set…
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- ISBN/ISSN
- 9780262257046
- Collation
- 1 online resource (xviii, 193 pages) : illustrations
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- Call Number
- 006 STO i
Unsupervised learning :foundations of neural computation
A Bradford book."OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 9780262288033
- Collation
- 1 online resource (xvi, 398 pages) :illustrations.
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Connectionist symbol processing
"A Bradford book.""Reprinted from Artificial intelligence, an international journal, volume 46, numbers 1-2, 1990"--Title page verso.The six contributions in Connectionist Symbol Processing address the current tension within the artificial intelligence community between advocates of powerful symbolic representations that lack efficient learning procedures and advocates of relatively simple lear…
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- ISBN/ISSN
- 9780262256360
- Collation
- 1 online resource (262 pages) :illustrations.
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- Call Number
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Pattern recognition by self-organizing neural networks
Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, artificial intelligence, and neural networks in general. Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally imp…
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- ISBN/ISSN
- 9780262269896
- Collation
- 1 online resource (691 pages) :illustrations
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Discovering the human connectome
A pioneer in the field outlines new empirical and computational approaches to mapping the neural connections of the human brain.OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 9780262305730
- Collation
- 1 online resource (xii, 232 pages) :illustrations
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An introduction to computational learning theory
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics.Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with th…
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- ISBN/ISSN
- 0585350531
- Collation
- 1 online resource (xii, 207 pages) :illustrations
- Series Title
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- Call Number
- 005 KEA i
Intelligence emerging : adaptivity and search in evolving neural systems
"Emergence--the formation of global patterns from solely local interactions--is a frequent and fascinating theme in the scientific literature both popular and academic. In this book, Keith Downing undertakes a systematic investigation of the widespread (if often vague) claim that intelligence is an emergent phenomenon. Downing focuses on neural networks, both natural and artificial, and how the…
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- ISBN/ISSN
- 0262328666
- Collation
- 1 online resource (xxii, 475 pages) :illustrations
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An introduction to neural networks
An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only cur…
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- ISBN/ISSN
- 9780262315883
- Collation
- 1 online resource (xi, 650 pages) : illustrations
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- -
- Call Number
- 001 AND i
How Smart Machines Think
The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these thingswork? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning t…
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- ISBN/ISSN
- 9780262347938
- Collation
- 1 online resource (xiv, 298 pages)
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Machine learning for data streams with practical examples in MOA
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 9780262346047
- Collation
- 1 online resource (xxi, 262 pages) :illustrations.
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