13. PKDD / 20. ECML 2009: Bled, Slovenia

Invited Talks (Abstracts)

• Shai Ben-David:
  Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges. 1
  
• Nello Cristianini:
  Are We There Yet?. 2
  
• Mark Greaves:
  The Growing Semantic Web. 3
  
• Rosie Jones:
  Privacy in Web Search Query Log Mining. 4
  
• Ralf Steinberger:
  Highly Multilingual News Analysis Applications. 5
  

Machine Learning Journal Abstracts

• Weiwei Cheng, Eyke Hüllermeier:
  Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. 6
  
• Thomas Gärtner, Shankar Vembu:
  On Structured Output Training: Hard Cases and an Efficient Alternative. 7
  
• Thorsten Joachims, Chun-Nam John Yu:
  Sparse Kernel SVMs via Cutting-Plane Training. 8
  
• Jeffrey Johns, Marek Petrik, Sridhar Mahadevan:
  Hybrid Least-Squares Algorithms for Approximate Policy Evaluation. 9
  
• Alexander Liu, Goo Jun, Joydeep Ghosh:
  A Self-training Approach to Cost Sensitive Uncertainty Sampling. 10
  
• Dan Roth, Rajhans Samdani:
  Learning Multi-linear Representations of Distributions for Efficient Inference. 11
  
• Raúl Santos-Rodríguez, Alicia Guerrero-Curieses, Rocío Alaíz-Rodríguez, Jesús Cid-Sueiro:
  Cost-Sensitive Learning Based on Bregman Divergences. 12
  

Data Mining and Knowledge Discovery Journal Abstracts

• Leman Akoglu, Christos Faloutsos:
  RTG: A Recursive Realistic Graph Generator Using Random Typing. 13-28
  
• Francesco Bonchi, Carlos Castillo, Debora Donato, Aristides Gionis:
  Taxonomy-Driven Lumping for Sequence Mining. 29
  
• Henrik Grosskreutz, Stefan Rüping:
  On Subgroup Discovery in Numerical Domains. 30
  
• Philipp Kranen, Thomas Seidl:
  Harnessing the Strengths of Anytime Algorithms for Constant Data Streams. 31
  
• Matthijs van Leeuwen, Jilles Vreeken, Arno Siebes:
  Identifying the Components. 32
  
• Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä, Matej Oresic, Samuel Kaski:
  Two-Way Analysis of High-Dimensional Collinear Data. 33
  
• Qiang-Li Zhao, Yan-Huang Jiang, Ming Xu:
  A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process. 34
  

Regular Papers

• Tarek Abudawood, Peter Flach:
  Evaluation Measures for Multi-class Subgroup Discovery. 35-50
  
• Érick Alphonse, Aomar Osmani:
  Empirical Study of Relational Learning Algorithms in the Phase Transition Framework. 51-66
  
• Loulwah AlSumait, Daniel Barbará, James Gentle, Carlotta Domeniconi:
  Topic Significance Ranking of LDA Generative Models. 67-82
  
• Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi:
  Communication-Efficient Classification in P2P Networks. 83-98
  
• Ai Azuma, Yuji Matsumoto:
  A Generalization of Forward-Backward Algorithm. 99-114
  
• Michele Berlingerio, Francesco Bonchi, Björn Bringmann, Aristides Gionis:
  Mining Graph Evolution Rules. 115-130
  
• Eva Besada-Portas, Sergey M. Plis, Jesús Manuel de la Cruz, Terran Lane:
  Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks. 131-146
  
• Albert Bifet, Ricard Gavaldà:
  Adaptive XML Tree Classification on Evolving Data Streams. 147-162
  
• Mirko Böttcher, Martin Spott, Rudolf Kruse:
  A Condensed Representation of Itemsets for Analyzing Their Evolution over Time. 163-178
  
• Mario Boley, Henrik Grosskreutz:
  Non-redundant Subgroup Discovery Using a Closure System. 179-194
  
• Jean-Cédric Chappelier, Emmanuel Eckard:
  PLSI: The True Fisher Kernel and beyond. 195-210
  
• Yanhua Chen, Lijun Wang, Ming Dong:
  Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization. 211-226
  
• Michal Aharon, Gilad Barash, Ira Cohen, Eli Mordechai:
  One Graph Is Worth a Thousand Logs: Uncovering Hidden Structures in Massive System Event Logs. 227-243
  
• Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad:
  Conference Mining via Generalized Topic Modeling. 244-259
  
• Christian Desrosiers, George Karypis:
  Within-Network Classification Using Local Structure Similarity. 260-275
  
• Paramveer S. Dhillon, Brian Tomasik, Dean P. Foster, Lyle H. Ungar:
  Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC). 276-289
  
• Tom Diethe, Zakria Hussain:
  Kernel Polytope Faces Pursuit. 290-301
  
• Jorge Díez, Juan José del Coz, Antonio Bahamonde, Oscar Luaces:
  Soft Margin Trees. 302-314
  
• Huyen Do, Alexandros Kalousis, Melanie Hilario:
  Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs. 315-329
  
• Huyen Do, Alexandros Kalousis, Adam Woznica, Melanie Hilario:
  Margin and Radius Based Multiple Kernel Learning. 330-343
  
• Ilias N. Flaounas, Marco Turchi, Tijl De Bie, Nello Cristianini:
  Inference and Validation of Networks. 344-358
  
• Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy:
  Binary Decomposition Methods for Multipartite Ranking. 359-374
  
• Murat Can Ganiz, Nikita I. Lytkin, William M. Pottenger:
  Leveraging Higher Order Dependencies between Features for Text Classification. 375-390
  
• Alessandra Giordani, Alessandro Moschitti:
  Syntactic Structural Kernels for Natural Language Interfaces to Databases. 391-406
  
• Nico Görnitz, Marius Kloft, Ulf Brefeld:
  Active and Semi-supervised Data Domain Description. 407-422
  
• Derek Greene, Padraig Cunningham:
  A Matrix Factorization Approach for Integrating Multiple Data Views. 423-438
  
• Quanquan Gu, Jie Zhou:
  Transductive Classification via Dual Regularization. 439-454
  
• Gokhan Gulgezen, Zehra Cataltepe, Lei Yu:
  Stable and Accurate Feature Selection. 455-468
  
• Hirotaka Hachiya, Jan Peters, Masashi Sugiyama:
  Efficient Sample Reuse in EM-Based Policy Search. 469-484
  
• Huseyin Hakkoymaz, Georgios Chatzimilioudis, Dimitrios Gunopulos, Heikki Mannila:
  Applying Electromagnetic Field Theory Concepts to Clustering with Constraints. 485-500
  
• Yanjun Han, Jue Wang:
  An l1 Regularization Framework for Optimal Rule Combination. 501-516
  
• Gregor Heinrich:
  A Generic Approach to Topic Models. 517-532
  
• Thibault Helleputte, Pierre Dupont:
  Feature Selection by Transfer Learning with Linear Regularized Models. 533-547
  
• Arjen Hommersom, Nivea de Carvalho Ferreira, Peter J. F. Lucas:
  Integrating Logical Reasoning and Probabilistic Chain Graphs. 548-563
  
• Tuyen N. Huynh, Raymond J. Mooney:
  Max-Margin Weight Learning for Markov Logic Networks. 564-579
  
• Dino Ienco, Ruggero G. Pensa, Rosa Meo:
  Parameter-Free Hierarchical Co-clustering by n-Ary Splits. 580-595
  
• Daisuke Ikeda, Einoshin Suzuki:
  Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts. 596-611
  
• Takashi Isozaki, Maomi Ueno:
  Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks. 612-627
  
• Sebastian Jaimungal, Eddie K. H. Ng:
  Kernel-Based Copula Processes. 628-643
  
• Nicholas K. Jong, Peter Stone:
  Compositional Models for Reinforcement Learning. 644-659
  
• Tobias Jung, Peter Stone:
  Feature Selection for Value Function Approximation Using Bayesian Model Selection. 660-675
  
• Kristian Kersting, Zhao Xu:
  Learning Preferences with Hidden Common Cause Relations. 676-691
  
• Marius Kloft, Shinichi Nakajima, Ulf Brefeld:
  Feature Selection for Density Level-Sets. 692-704
  
• Levente Kocsis, András György:
  Efficient Multi-start Strategies for Local Search Algorithms. 705-720
  
• Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillemin, Christophe Meyer:
  Considering Unseen States as Impossible in Factored Reinforcement Learning. 721-735
  
• Tobias Lang, Marc Toussaint:
  Relevance Grounding for Planning in Relational Domains. 736-751