Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings. Part I / Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný (eds.)
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 invite...
Saved in:
Online Access: |
Full Text (via Springer) |
---|---|
Corporate Author: | |
Other Authors: | |
Other title: | ECML PKDD 2013. |
Format: | Conference Proceeding eBook |
Language: | English |
Published: |
Heidelberg :
Springer,
2013.
|
Series: | Lecture notes in computer science ;
8188. LNCS sublibrary. Artificial intelligence. Lecture notes in computer science. Lecture notes in artificial intelligence. |
Subjects: |
MARC
LEADER | 00000cam a2200000xi 4500 | ||
---|---|---|---|
001 | b7595580 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 130911s2013 gw a o 101 0 eng d | ||
005 | 20240418150158.2 | ||
019 | |a 859590006 |a 1069635197 | ||
020 | |a 9783642409882 |q (electronic bk.) | ||
020 | |a 3642409881 |q (electronic bk.) | ||
020 | |a 3642409873 | ||
020 | |a 9783642409875 | ||
020 | |z 9783642409875 | ||
024 | 7 | |a 10.1007/978-3-642-40988-2 | |
035 | |a (OCoLC)spr857816953 | ||
035 | |a (OCoLC)857816953 |z (OCoLC)859590006 |z (OCoLC)1069635197 | ||
037 | |a spr978-3-642-40988-2 | ||
040 | |a GW5XE |b eng |e rda |e pn |c GW5XE |d YDXCP |d EMU |d COO |d ZMC |d OHS |d OCLCA |d OCLCF |d OCLCO |d OCLCQ |d OCLCO |d NUI |d OCL |d OCLCO |d EBLCP |d OCLCQ |d OCLCO |d DIBIB |d OCLCO |d JG0 |d MERER |d DGU |d ESU |d OCLCQ |d IOG |d OCLCO |d OCLCA |d BUF |d OCLCO |d CEF |d CRU |d OCLCQ |d OCLCO |d TFW |d OCLCO |d U3W |d OCLCA |d WYU |d YOU |d UWO |d TKN |d OCLCO |d OCLCQ |d OCLCA |d OCLCQ |d OCLCA |d AJS |d OCLCQ | ||
049 | |a GWRE | ||
050 | 4 | |a Q325.5 |b .E26 2013 | |
111 | 2 | |a ECML PKDD (Conference) |d (2013 : |c Prague, Czech Republic) |0 http://id.loc.gov/authorities/names/nb2013020938. | |
245 | 1 | 0 | |a Machine learning and knowledge discovery in databases : |b European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings. |n Part I / |c Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný (eds.) |
246 | 3 | |a ECML PKDD 2013. | |
264 | 1 | |a Heidelberg : |b Springer, |c 2013. | |
300 | |a 1 online resource (liv, 691 pages) : |b illustrations. | ||
336 | |a text |b txt |2 rdacontent. | ||
337 | |a computer |b c |2 rdamedia. | ||
338 | |a online resource |b cr |2 rdacarrier. | ||
347 | |a text file. | ||
347 | |b PDF. | ||
490 | 1 | |a Lecture notes in computer science, |x 0302-9743. | |
490 | 1 | |a Lecture notes in artificial intelligence ; |v 8188. | |
490 | 1 | |a LNCS sublibrary. SL 7, Artificial intelligence. | |
505 | 0 | 0 | |t Reinforcement Learning. |t A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning / |r Edouard Klein ... et al. -- |t Learning from Demonstrations: Is It Worth Estimating a Reward Function? / |r Bilal Piot, Matthieu Geist, Olivier Pietquin -- |t Recognition of Agents Based on Observation of Their Sequential Behavior / |r Qifeng Qiao, Peter A. Beling -- |t Learning Throttle Valve Control Using Policy Search / |r Bastian Bischoff ... et al. -- |t Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System / |r Daniel Urieli, Peter Stone -- |t Learning Graph-Based Representations for Continuous Reinforcement Learning Domains / |r Jan Hendrik Metzen -- |t Regret Bounds for Reinforcement Learning with Policy Advice / |r Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill -- |t Exploiting Multi-step Sample Trajectories for Approximate Value Iteration / |r Robert Wright ... et al. |
505 | 8 | 0 | |t Markov Decision Processes. |t Expectation Maximization for Average Reward Decentralized POMDPs / |r Joni Pajarinen, Jaakko Peltonen -- |t Properly Acting under Partial Observability with Action Feasibility Constraints / |r Caroline P. Carvalho Chanel, Florent Teichteil-Königsbuch -- |t Iterative Model Refinement of Recommender MDPs Based on Expert Feedback / |r Omar Zia Khan, Pascal Poupart, John Mark Agosta -- |t Solving Relational MDPs with Exogenous Events and Additive Rewards / |r Saket Joshi ... et al. -- |t Continuous Upper Confidence Trees with Polynomial Exploration -- Consistency / |r David Auger, Adrien Couëtoux, Olivier Teytaud. |
505 | 8 | 0 | |t Active Learning and Optimization. |t A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization / |r Ali Jalali ... et al. -- |t Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration / |r Emile Contal ... et al. -- |t Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization / |r Philip Bachman, Doina Precup -- |t A Time and Space Efficient Algorithm for Contextual Linear Bandits / |r José Bento ... et al. -- |t Knowledge Transfer for Multi-labeler Active Learning / |r Meng Fang, Jie Yin, Xingquan Zhu. |
505 | 8 | 0 | |t Learning from Sequences. |t Spectral Learning of Sequence Taggers over Continuous Sequences / |r Adrià Recasens, Ariadna Quattoni -- |t Fast Variational Bayesian Linear State-Space Model / |r Jaakko Luttinen -- |t Inhomogeneous Parsimonious Markov Models / |r Ralf Eggeling ... et al. -- |t Explaining Interval Sequences by Randomization / |r Andreas Henelius, Jussi Korpela, Kai Puolamäki -- |t Itemset Based Sequence Classification / |r Cheng Zhou, Boris Cule, Bart Goethals -- |t A Relevance Criterion for Sequential Patterns / |r Henrik Grosskreutz, Bastian Lang, Daniel Trabold -- |t A Fast and Simple Method for Mining Subsequences with Surprising Event Counts / |r Jefrey Lijffijt -- |t Relevant Subsequence Detection with Sparse Dictionary Learning / |r Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey. |
505 | 8 | 0 | |t Time Series and Spatio-temporal Data. |t Future Locations Prediction with Uncertain Data / |r Disheng Qiu, Paolo Papotti, Lorenzo Blanco -- |t Modeling Short-Term Energy Load with Continuous Conditional Random Fields / |r Hongyu Guo. |
505 | 8 | 0 | |t Data Streams. |t Fault Tolerant Regression for Sensor Data / |r Indrė Žliobaitė, Jaakko Hollmén -- |t Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them / |r Albert Bifet ... et al. -- |t Adaptive Model Rules from Data Streams / |r Ezilda Almeida, Carlos Ferreira, João Gama -- |t Fast and Exact Mining of Probabilistic Data Streams / |r Reza Akbarinia, Florent Masseglia. |
505 | 8 | 0 | |t Graphs and Networks. |t Detecting Bicliques in GF[q] / |r Jan Ramon, Pauli Miettinen, Jilles Vreeken -- |t As Strong as the Weakest Link:Mining Diverse Cliques in Weighted Graphs / |r Petko Bogdanov ... et al. -- |t How Robust Is the Core of a Network? / |r Abhijin Adiga, Anil Kumar S. Vullikanti -- |t Community Distribution Outlier Detection in Heterogeneous Information Networks / |r Manish Gupta, Jing Gao, Jiawei Han -- |t Protein Function Prediction Using Dependence Maximization / |r Guoxian Yu ... et al. -- |t Improving Relational Classification Using Link Prediction Techniques / |r Cristina Pérez-Solà, Jordi Herrera-Joancomartí -- |t A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data / |r Gerben K.D. de Vries -- |t Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width / |r Tamás Horváth, Keisuke Otaki, Jan Ramon -- |t Continuous Similarity Computation over Streaming Graphs / |r Elena Valari, Apostolos N. Papadopoulos -- |t Trend Mining in Dynamic Attributed Graphs / |r Elise Desmier ... et al. -- |t Sparse Relational Topic Models for Document Networks / |r Aonan Zhang, Jun Zhu, Bo Zhang. |
500 | |a International conference proceedings. | ||
500 | |a Includes author index. | ||
520 | |a 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. | ||
588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed September 3, 2013) | |
650 | 0 | |a Machine learning |v Congresses. |0 http://id.loc.gov/authorities/subjects/sh2008107143. | |
650 | 0 | |a Data mining |v Congresses. |0 http://id.loc.gov/authorities/subjects/sh2008102035. | |
650 | 7 | |a Data mining. |2 fast |0 (OCoLC)fst00887946. | |
650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795. | |
655 | 7 | |a Conference papers and proceedings. |2 fast |0 (OCoLC)fst01423772. | |
700 | 1 | |a Blockeel, Hendrik, |e editor. |0 http://id.loc.gov/authorities/names/nb2008008251 |1 http://isni.org/isni/0000000424665824. | |
776 | 0 | 8 | |i Printed edition: |z 9783642409875. |
856 | 4 | 0 | |u https://colorado.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-642-40988-2 |z Full Text (via Springer) |
830 | 0 | |a Lecture notes in computer science ; |v 8188. |0 http://id.loc.gov/authorities/names/n42015162. | |
830 | 0 | |a LNCS sublibrary. |n SL 7, |p Artificial intelligence. |0 http://id.loc.gov/authorities/names/n2008077786. | |
830 | 0 | |a Lecture notes in computer science. |p Lecture notes in artificial intelligence. |0 http://id.loc.gov/authorities/names/n86736436. | |
907 | |a .b75955805 |b 05-04-22 |c 11-06-13 | ||
915 | |a - | ||
998 | |a web |b 01-31-22 |c b |d b |e - |f eng |g gw |h 0 |i 1 | ||
907 | |a .b75955805 |b 01-31-22 |c 11-06-13 | ||
944 | |a MARS - RDA ENRICHED | ||
956 | |b Springer Nature - Springer Computer Science eBooks 2013 English International | ||
956 | |a Springer e-books | ||
956 | |b Springer Nature - Springer Computer Science eBooks 2013 English International | ||
999 | f | f | |i 71be22ff-fc2a-55f9-8ea9-daa8f296356d |s b5c48d43-b73b-5087-84df-a822f384408a |
952 | f | f | |p Can circulate |a University of Colorado Boulder |b Online |c Online |d Online |e Q325.5 .E26 2013 |h Library of Congress classification |i Ebooks, Prospector |n 1 |