15. PKDD / 22. ECML 2011: Athens, Greece

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

• Riad Akrour, Marc Schoenauer, Michèle Sebag:
  Preference-Based Policy Learning. 12-27
  
• 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
  
• Gerasimos Antzoulatos, Michael N. Vrahatis:
  α-Clusterable Sets. 108-123
  
• Hiromi Arai, Jun Sakuma:
  Privacy Preserving Semi-supervised Learning for Labeled Graphs. 124-139
  
• 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
  
• Eraldo R. Fernandes, Ulf Brefeld:
  Learning from Partially Annotated Sequences. 407-422
  
• 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
  
• Quanquan Gu, Zhenhui Li, Jiawei Han:
  Linear Discriminant Dimensionality Reduction. 549-564
  
• 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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