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...
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| Other title: | ECML PKDD 2013. |
| Format: | Conference Proceeding eBook |
| Language: | English |
| Published: |
Heidelberg :
Springer,
2013.
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| Series: | Lecture notes in computer science ;
8188. LNCS sublibrary. Artificial intelligence. Lecture notes in computer science. Lecture notes in artificial intelligence. |
| Subjects: |
MARC
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| 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. | |
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| 490 | 1 | |a Lecture notes in artificial intelligence ; |v 8188. | |
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| 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) | |
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| 700 | 1 | |a Blockeel, Hendrik, |e editor. |0 http://id.loc.gov/authorities/names/nb2008008251 |1 http://isni.org/isni/0000000424665824. | |
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