TY  - BOOK
AU  - Blockeel,Hendrik
AU  - Kersting,Kristian
AU  - Nijssen,Siegfried
AU  - Železný,Filip
ED  - SpringerLink (Online service)
TI  - Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I 
T2  - Lecture Notes in Computer Science,
SN  - 9783642409882
AV  - QA76.9.D343 
U1  - 006.312 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Computer Science
KW  - Computational complexity
KW  - Data mining
KW  - Information storage and retrieval systems
KW  - Artificial intelligence
KW  - Optical pattern recognition
KW  - Data Mining and Knowledge Discovery
KW  - Artificial Intelligence (incl. Robotics)
KW  - Pattern Recognition
KW  - Discrete Mathematics in Computer Science
KW  - Probability and Statistics in Computer Science
KW  - Information Storage and Retrieval
N1  - 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
N2  - 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; medical applications; nectar track; demo track
UR  - http://dx.doi.org/10.1007/978-3-642-40988-2
ER  -