Statistical Learning and Data Sciences [electronic resource] : Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings / edited by Alexander Gammerman, Vladimir Vovk, Harris Papadopoulos.
Contributor(s): Gammerman, Alexander [editor.] | Vovk, Vladimir [editor.] | Papadopoulos, Harris [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 9047Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XIV, 444 p. 133 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319170916.Subject(s): Computer science | Computers | Algorithms | Database management | Information storage and retrieval | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Algorithm Analysis and Problem Complexity | Information Systems Applications (incl. Internet) | Database Management | Computation by Abstract Devices | Information Storage and RetrievalAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015, held in Egham, Surrey, UK, April 2015. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on statistical learning and its applications, conformal prediction and its applications, new frontiers in data analysis for nuclear fusion, and geometric data analysis.
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This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015, held in Egham, Surrey, UK, April 2015. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on statistical learning and its applications, conformal prediction and its applications, new frontiers in data analysis for nuclear fusion, and geometric data analysis.
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