Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis (Eds.): Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I. Springer 2011 Lecture Notes in Computer Science ISBN 978-3-642-23779-9
Invited Talks (Abstracts)
- Rakesh Agrawal: Enriching Education through Data Mining. 1-2
- Albert-László Barabási: Human Dynamics: From Human Mobility to Predictability. 3
- Christopher M. Bishop: Embracing Uncertainty: Applied Machine Learning Comes of Age. 4
- Andrei Z. Broder: Highly Dimensional Problems in Computational Advertising. 5
- Marco Gori: Learning from Constraints. 6
- Heikki Mannila: Permutation Structure in 0-1 Data. 7
Industrial Invited Talks (Abstracts)
- Vasilis Aggelis: Reading Customers Needs and Expectations with Analytics. 8
- Radu Jurca: Algorithms and Challenges on the GeoWeb. 9
- Neel Sundaresan: Data Science and Machine Learning at Scale. 10
- Olivier Verscheure: Smart Cities: How Data Mining and Optimization Can Shape Future Cities. 11
Regular Papers
- Kais Allab, Khalid Benabdeslem: Constraint Selection for Semi-supervised Topological Clustering. 28-43
- Hélio Almeida, Dorgival Olavo Guedes Neto, Wagner Meira Jr., Mohammed J. Zaki: Is There a Best Quality Metric for Graph Clusters? 44-59
- Samir Al-Stouhi, Chandan K. Reddy: Adaptive Boosting for Transfer Learning Using Dynamic Updates. 60-75
- Aris Anagnostopoulos, George Brova, Evimaria Terzi: Peer and Authority Pressure in Information-Propagation Models. 76-91
- Rajul Anand, Chandan K. Reddy: Constrained Logistic Regression for Discriminative Pattern Mining. 92-107
- Muhammad Awais, Fei Yan, Krystian Mikolajczyk, Josef Kittler: Novel Fusion Methods for Pattern Recognition. 140-155
- Borja Balle, Ariadna Quattoni, Xavier Carreras: A Spectral Learning Algorithm for Finite State Transducers. 156-171
- Nicola Barbieri, Giuseppe Manco: An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering. 172-187
- Aurélien Bellet, Amaury Habrard, Marc Sebban: Learning Good Edit Similarities with Generalization Guarantees. 188-203
- Khalid Benabdeslem, Mohammed Hindawi: Constrained Laplacian Score for Semi-supervised Feature Selection. 204-218
- Alberto Bertoni, Marco Frasca, Giorgio Valentini: COSNet: A Cost Sensitive Neural Network for Semi-supervised Learning in Graphs. 219-234
- Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer: Regularized Sparse Kernel Slow Feature Analysis. 235-248
- Gianluca Bontempi, Olivier Caelen: A Selecting-the-Best Method for Budgeted Model Selection. 249-262
- Róbert Busa-Fekete, Balázs Kégl, Tamás Éltetö, György Szarvas: A Robust Ranking Methodology Based on Diverse Calibration of AdaBoost. 263-279
- Tianyu Cao, Xindong Wu, Xiaohua Tony Hu, Song Wang: Active Learning of Model Parameters for Influence Maximization. 280-295
- Changyou Chen, Lan Du, Wray L. Buntine: Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process. 296-311
- Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park: Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. 312-327
- Boris Chidlovskii: Learning Recommendations in Social Media Systems by Weighting Multiple Relations. 328-342
- Stéphan Clémençon, Romaric Gaudel, Jérémie Jakubowicz: Clustering Rankings in the Fourier Domain. 343-358
- Nicolas Courty, Thomas Burger, Johann Laurent: PerTurbo: A New Classification Algorithm Based on the Spectrum Perturbations of the Laplace-Beltrami Operator. 359-374
- Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari: Datum-Wise Classification: A Sequential Approach to Sparsity. 375-390
- Mehrdad Farajtabar, Amirreza Shaban, Hamid Reza Rabiee, Mohammad H. Rohban: Manifold Coarse Graining for Online Semi-supervised Learning. 391-406
- Mario Frank, Morteza Haghir Chehreghani, Joachim M. Buhmann: The Minimum Transfer Cost Principle for Model-Order Selection. 423-438
- Valdinei Freire da Silva, Anna Helena Reali Costa: A Geometric Approach to Find Nondominated Policies to Imprecise Reward MDPs. 439-454
- Benoît Frénay, Gael de Lannoy, Michel Verleysen: Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs. 455-470
- Zhouyu Fu, Guojun Lu, Kai Ming Ting, Dengsheng Zhang: Building Sparse Support Vector Machines for Multi-Instance Classification. 471-486
- Thomas Furmston, David Barber: Lagrange Dual Decomposition for Finite Horizon Markov Decision Processes. 487-502
- Vincent Graziano, Jan Koutník, Jürgen Schmidhuber: Unsupervised Modeling of Partially Observable Environments. 503-515
- Mihajlo Grbovic, Slobodan Vucetic: Tracking Concept Change with Incremental Boosting by Minimization of the Evolving Exponential Loss. 516-532
- Henrik Grosskreutz, Daniel Paurat: Fast and Memory-Efficient Discovery of the Top-k Relevant Subgroups in a Reduced Candidate Space. 533-548
- Stephan Günnemann, Brigitte Boden, Thomas Seidl: DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors. 565-580
- Bernd Gutmann, Ingo Thon, Luc De Raedt: Learning the Parameters of Probabilistic Logic Programs from Interpretations. 581-596
- Roberto Guzmán-Martínez, Rocío Alaíz-Rodríguez: Feature Selection Stability Assessment Based on the Jensen-Shannon Divergence. 597-612
- Robert Gwadera, Gianluca Antonini, Abderrahim Labbi: Mining Actionable Partial Orders in Collections of Sequences. 613-628
- Maria Halkidi, Iordanis Koutsopoulos: A Game Theoretic Framework for Data Privacy Preservation in Recommender Systems. 629-644
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