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Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II / edited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 8189
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 8189
- Language:
- English
- Subjects (All):
- Data mining.
- Artificial intelligence.
- Pattern recognition systems.
- Computer science-Mathematics.
- Discrete mathematics.
- Mathematical statistics.
- Information storage and retrieval systems.
- Data Mining and Knowledge Discovery.
- Artificial Intelligence.
- Automated Pattern Recognition.
- Discrete Mathematics in Computer Science.
- Probability and Statistics in Computer Science.
- Information Storage and Retrieval.
- Local Subjects:
- Data Mining and Knowledge Discovery.
- Artificial Intelligence.
- Automated Pattern Recognition.
- Discrete Mathematics in Computer Science.
- Probability and Statistics in Computer Science.
- Information Storage and Retrieval.
- Physical Description:
- 1 online resource (XLIV, 693 pages) : 160 illustrations
- Edition:
- 1st ed. 2013.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
- System Details:
- text file PDF
- Summary:
- 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.
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-642-40991-2
- 9783642409912
- Access Restriction:
- Restricted for use by site license.
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