Settles Burr (12 results)
Language: English
Published by Springer International Publishing AG, CH, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- First Edition
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Paperback. Condition: New. 1st. The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose "queries," usually in the form of unlabeled data instances to be labeled by an "oracle" (e.g., a human… annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or "query selection frameworks." We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Condition: New. In English.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
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Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose 'queries,' usually in the form of unlabeled data ins…tances to be labeled by an 'oracle' (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or 'query selection frameworks.' We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Active Learning | Burr Settles | Taschenbuch | Synthesis Lectures on Artificial Intelligence and Machine Learning | xiv | Englisch | 2012 | Springer | EAN 9783031004322 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot…]com | Anbieter: preigu.
Language: English
Published by Springer International Publishing AG, CH, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- First Edition
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Paperback. Condition: New. 1st. The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose "queries," usually in the form of unlabeled data instances to be labeled by an "oracle" (e.g., a human… annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or "query selection frameworks." We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Language: English
Published by Springer International Publishing Aug 2012, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose 'queries,' usually in the form of un…labeled data instances to be labeled by an 'oracle' (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or 'query selection frameworks.' We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations 116 pp. Englisch.
Language: English
Published by Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Language: English
Published by Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose queries, usually in t…he form of unlabeled data instances to.
Language: English
Published by Springer, Springer Aug 2012, 2012
Series: Book 2 of 14 - Synthesis Lectures on Artificial Intelligence and Machine Learning
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose 'queries,' usually in the form of unlabe…led data instances to be labeled by an 'oracle' (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or 'query selection frameworks.' We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical ConsiderationsSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 116 pp. Englisch.
