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Art, science, and the politics of knowledge
"Introduces a new field of study adapted from STS that the author refers to as art, science, and technology studies"--OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 0262369583
- Collation
- 1 online resource.
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The distributed classroom
"Joyner and Isbell describe a model for higher education -- the distributed classroom -- that combines the best aspects of traditional college attendance with the accessibility of online classes"--OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 0262366568
- Collation
- 1 online resource.
- Series Title
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- Call Number
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Art in the age of machine learning
"This book examines artistic practices that use machine learning and computational technologies through historical perspectives surrounding adaptive systems from the 1950s onwards"--OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 0262367092
- Collation
- 1 online resource.
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How to grow a robot: :developing human-friendly, social AI
"Mark Lee considers that the current gains in machine learning and deep learning will not produce robots that can interact effectively with humans. The book then explores how robots can become more human-like, more general-purpose, and more social. The book introduces us to the core ideas in Developmental Robotics - showing how this new approach can "grow" robots through (their own) experience …
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- ISBN/ISSN
- 0262357852
- Collation
- 1 online resource.
- Series Title
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- Call Number
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Language in our brain :the origins of a uniquely human capacity
A comprehensive account of the neurobiological basis of language, arguing that species-specific brain differences may be at the root of the human capacity for language.OCLC-licensed vendor bibliographic record.
- Edition
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- ISBN/ISSN
- 9780262342964
- Collation
- 1 online resource
- Series Title
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Computer games for learning :an evidence-based approach
Many strong claims are made for the educational value of computer games, but there is a need for systematic examination of the research evidence that might support such claims. This book fills that need by providing, a comprehensive and up-to-date investigation of what research shows about learning with computer games. Computer Games for Learning describes three genres of game research: the val…
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- ISBN/ISSN
- 0262324504
- Collation
- 1 online resource (xvii, 281 pages)
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Predicting structured data
Collected papers based on talks presented at two Neural Information Processing Systems workshops.State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must sati…
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- ISBN/ISSN
- 9780262255691
- Collation
- 1 online resource (viii, 348 pages) :illustrations.
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Large-scale kernel machines
Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset o…
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- ISBN/ISSN
- 0262255790
- Collation
- 1 online resource (xii, 396 pages) :illustrations.
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Learning with kernels :support vector machines, regularization, optimization,…
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by…
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- ISBN/ISSN
- 9780262256933
- Collation
- 1 online resource (xviii, 626 pages) :illustrations.
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Learning kernel classifiers :theory and algorithms
Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This…
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- ISBN/ISSN
- 9780262256339
- Collation
- 1 online resource (xx, 364 pages) :illustrations.
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