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Found 163 from your keywords: subject="MACHINE"
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cover
Multiple-Aspect Analysis of Semantic Trajectories: First International Worksh…
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MATWIN, StanTSERPES, KonstantinosRENSO, Chiara

This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full papers presented were carefully rev…

Edition
1
ISBN/ISSN
9783030380816
Collation
IX, 133
Series Title
-
Call Number
-
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cover
Foundation Models for Natural Language Processing
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Gerhard Paaß, Sven Giesselbach

This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documen…

Edition
1
ISBN/ISSN
978-3-031-23190-2
Collation
-
Series Title
Artificial Intelligence: Foundations, Theory, and Algorithms
Call Number
XVIII, 436
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cover
Integrating Data Science and Earth Science
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Bouwer,Laurens M.Dransch,DorisRuhnke,RolandRechid,DianaFrickenhaus,StephanGreinert,Jens

This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.

Edition
-
ISBN/ISSN
978-3-030-99546-1
Collation
-
Series Title
-
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-
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cover
xxAI - Beyond Explainable AI
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Andreas Holzinger

Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and …

Edition
1
ISBN/ISSN
-
Collation
-
Series Title
Lecture Notes in Computer Science
Call Number
X, 397
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cover
The materiality of interaction :notes on the materials of interaction design
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M.I.T. Press,Wiberg, Mikael,

A new approach to interaction design that moves beyond representation and metaphor to focus on the material manifestations of interaction. Smart watches, smart cars, the Internet of things, 3D printing: all signal a trend toward combining digital and analogue materials in design. Interaction with these new hybrid forms is increasingly mediated through physical materials, and therefore interacti…

Edition
-
ISBN/ISSN
9780262344692
Collation
1 online resource (ix, 192 pages) :illustrations
Series Title
-
Call Number
-
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cover
Machine learners :archaeology of a data practice
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Mackenzie, Adrian,

Machine learning - programming computers to learn from data - has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as oper…

Edition
-
ISBN/ISSN
9780262342551
Collation
1 online resource (xvi, 252 pages) :illustrations
Series Title
-
Call Number
-
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cover
Boosting: Foundations and Algorithms
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Schapire, Robert E.Freund, Yoav

A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. …

Edition
-
ISBN/ISSN
9780262301183
Collation
1 online resource (xv, 526 pages) :illustrations
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-
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-
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cover
Gaussian processes for machine learning
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Rasmussen, Carl Edward.Williams, Christopher K. I.

"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, tar…

Edition
-
ISBN/ISSN
9780262256834
Collation
1 online resource (xviii, 248 pages) : illustrations.
Series Title
-
Call Number
510 RAS g
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cover
Learning Machine Translation
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Goutte, CyrilCancedda, NicolaDymetman, MarcFoster, George

This title looks at how machine learning can improve machine translation, enabling technologies and new statistical techniques.OCLC-licensed vendor bibliographic record.

Edition
-
ISBN/ISSN
9780262255097
Collation
1 online resource (xii, 316 pages) :illustrations.
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-
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-
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cover
Dataset Shift in Machine Learning
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Candela, Joaquin Quiñonero-Sugiyama, MasashiSchwaighofer, AntonLawrence, Neil D.

This work is an overview of recent efforts in the machine learning community to deal with dataset and covariate shift which occurs when test and training inputs and outputs have different distributions.OCLC-licensed vendor bibliographic record.

Edition
-
ISBN/ISSN
9780262255103
Collation
1 online resource (xv, 229 pages) :illustrations.
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-
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-
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