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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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Living and learning with new media :summary of findings from the digital yout…
This report summarizes the results of an ambitious three-year ethnographic study, funded by the John D. and Catherine T. MacArthur Foundation, into how young people are living and learning with new media in varied settings--at home, in after school programs, and in online spaces. It offers a condensed version of a longer treatment provided in the book Hanging Out, Messing Around, and Geeking Ou…
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- Kindle ed.
- ISBN/ISSN
- 9780262258937
- Collation
- 1 online resource (xx, 98 pages) :illustrations.
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Hanging out, messing around, and geeking out :kids living and learning with n…
An examination of young people's everyday new media practices--including video-game playing, text-messaging, digital media production, and social media use. Conventional wisdom about young people's use of digital technology often equates generational identity with technology identity: today's teens seem constantly plugged in to video games, social networking sites, and text messaging. Yet there…
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- ISBN/ISSN
- 9780262258920
- Collation
- 1 online resource (xix, 419 pages) :illustrations.
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Scholarship in the digital age :information, infrastructure, and the Internet
Scholars in all fields now have access to an unprecedented wealth of online information, tools, and services. The Internet lies at the core of an information infrastructure for distributed, data-intensive, and collaborative research. Although much attention has been paid to the new technologies making this possible, from digitized books to sensor networks, it is the underlying social and policy…
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- ISBN/ISSN
- 9780262255783
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- 1 online resource (xxiv, 336 pages) :illustrations
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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
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- 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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The acquisition of syntactic knowledge
"This landmark work in computational linguistics is of great importance both theoretically and practically because it shows that much of English grammar can be learned by a simple program. The Acquisition of Syntactic Knowledge investigates the central questions of human and machine cognition: How do people learn language? How can we get a machine to learn language? It first presents an explici…
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- ISBN/ISSN
- 0585368910
- Collation
- 1 online resource (xii, 368 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
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- 1 online resource (xx, 364 pages) :illustrations.
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Learnability in optimality theory
AnnotationOCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 0585354677
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- 1 online resource (vi, 140 pages) :illustrations
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