Overview

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

Full Product Details

Author:   Hendrik Blockeel ,  Kristian Kersting ,  Siegfried Nijssen ,  Filip Železný
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2013 ed.
Volume:   8189
Dimensions:   Width: 15.50cm , Height: 4.10cm , Length: 23.50cm
Weight:   1.116kg
ISBN:  

9783642409905

ISBN 10:   3642409903
Pages:   693
Publication Date:   12 September 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Reinforcement learning.- Markov decision processes.- Active learning and optimization.- Learning from sequences.- Time series and spatio-temporal data.- Data streams.- Graphs and networks.- Social network analysis.- Natural language processing and information extraction.- Ranking and recommender systems.- Matrix and tensor analysis.- Structured output prediction, multi-label and multi-task learning.- Transfer learning.- Bayesian learning.- Graphical models.- Nearest-neighbor methods.- Ensembles.- Statistical learning.- Semi-supervised learning.- Unsupervised learning.- Subgroup discovery, outlier detection and anomaly detection.- Privacy and security.- Evaluation.- Applications.- Medical applications.

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