12. PKDD / 19. ECML 2008: Antwerp, Belgium

Invited Talks (Abstracts)

• Françoise Fogelman-Soulié:
  Industrializing Data Mining, Challenges and Perspectives. 1
  
• Yoav Freund:
  From Microscopy Images to Models of Cellular Processes. 2
  
• Anil K. Jain:
  Data Clustering: 50 Years Beyond K-means. 3-4
  
• Raymond J. Mooney:
  Learning Language from Its Perceptual Context. 5
  
• Raghu Ramakrishnan:
  The Role of Hierarchies in Exploratory Data Mining. 6
  

Machine Learning Journal Abstracts

• Christos Dimitrakakis, Michail G. Lagoudakis:
  Rollout Sampling Approximate Policy Iteration. 7
  
• Krishnamurthy Dvijotham, Soumen Chakrabarti, Subhasis Chaudhuri:
  New Closed-Form Bounds on the Partition Function. 8
  
• Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik:
  Large Margin vs. Large Volume in Transductive Learning. 9-10
  
• Ankur Jain, Daniel Nikovski:
  Incremental Exemplar Learning Schemes for Classification on Embedded Devices. 11
  
• Heng Luo, Changyong Niu, Ruimin Shen, Carsten Ullrich:
  A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarity. 12
  
• Stijn Vanderlooy, Eyke Hüllermeier:
  A Critical Analysis of Variants of the AUC. 13
  
• Markus Weimer, Alexandros Karatzoglou, Alex J. Smola:
  Improving Maximum Margin Matrix Factorization. 14
  

Data Mining and Knowledge Discovery Journal Abstracts

• Petteri Hintsanen, Hannu Toivonen:
  Finding Reliable Subgraphs from Large Probabilistic Graphs. 15
  
• Adrian Kügel, Enno Ohlebusch:
  A Space Efficient Solution to the Frequent String Mining Problem for Many Databases. 16
  
• Pauli Miettinen:
  The Boolean Column and Column-Row Matrix Decompositions. 17
  
• Apostolos N. Papadopoulos, Apostolos Lyritsis, Yannis Manolopoulos:
  SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs. 18
  
• Chedy Raïssi, Toon Calders, Pascal Poncelet:
  Mining Conjunctive Sequential Patterns. 19
  
• Arnaud Soulet, Bruno Crémilleux:
  Adequate Condensed Representations of Patterns. 20-21
  
• Jimeng Sun, Charalampos E. Tsourakakis, Evan Hoke, Christos Faloutsos, Tina Eliassi-Rad:
  Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Data. 22
  

Regular Papers

• Rezwan Ahmed, Huzefa Rangwala, George Karypis:
  TOPTMH: Topology Predictor for Transmembrane alpha-Helices. 23-38
  
• Jaime Alonso, Juan José del Coz, Jorge Díez, Oscar Luaces, Antonio Bahamonde:
  Learning to Predict One or More Ranks in Ordinal Regression Tasks. 39-54
  
• Hock Hee Ang, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng:
  Cascade RSVM in Peer-to-Peer Networks. 55-70
  
• Andreas Argyriou, Andreas Maurer, Massimiliano Pontil:
  An Algorithm for Transfer Learning in a Heterogeneous Environment. 71-85
  
• José L. Balcázar:
  Minimum-Size Bases of Association Rules. 86-101
  
• Yaxin Bi, Shengli Wu, Xuhui Shen, Pan Xiong:
  Combining Classifiers through Triplet-Based Belief Functions. 102-116
  
• Jinbo Bi, Tao Xiong, Shipeng Yu, Murat Dundar, R. Bharat Rao:
  An Improved Multi-task Learning Approach with Applications in Medical Diagnosis. 117-132
  
• Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton:
  Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis. 133-145
  
• Antoine Bordes, Nicolas Usunier, Léon Bottou:
  Sequence Labelling SVMs Trained in One Pass. 146-161
  
• Jérôme Callut, Kevin Françoisse, Marco Saerens, Pierre Dupont:
  Semi-supervised Classification from Discriminative Random Walks. 162-177
  
• Bin Cao, Jian-Tao Sun, Jianmin Wu, Qiang Yang, Zheng Chen:
  Learning Bidirectional Similarity for Collaborative Filtering. 178-194
  
• Andrew Carlson, Charles Schafer:
  Bootstrapping Information Extraction from Semi-structured Web Pages. 195-210
  
• Doran Chakraborty, Peter Stone:
  Online Multiagent Learning against Memory Bounded Adversaries. 211-226
  
• Boris Chidlovskii, Loïc Lecerf:
  Scalable Feature Selection for Multi-class Problems. 227-240
  
• David A. Cieslak, Nitesh V. Chawla:
  Learning Decision Trees for Unbalanced Data. 241-256
  
• Giorgio Corani, Marco Zaffalon:
  Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities. 257-271
  
• Trinh Minh Tri Do, Thierry Artières:
  A Fast Method for Training Linear SVM in the Primal. 272-287
  
• Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
  On the Equivalence of the SMO and MDM Algorithms for SVM Training. 288-300
  
• Wouter Duivesteijn, Ad Feelders:
  Nearest Neighbour Classification with Monotonicity Constraints. 301-316
  
• Eric Eaton, Marie desJardins, Terran Lane:
  Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer. 317-332
  
• Frank Eichinger, Klemens Böhm, Matthias Huber:
  Mining Edge-Weighted Call Graphs to Localise Software Bugs. 333-348
  
• Ana Maria Funes, César Ferri, José Hernández-Orallo, M. José Ramírez-Quintana:
  Hierarchical Distance-Based Conceptual Clustering. 349-364
  
• Andrés Gago Alonso, José E. Medina-Pagola, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez Trinidad:
  Mining Frequent Connected Subgraphs Reducing the Number of Candidates. 365-376
  
• Alvina Goh, René Vidal:
  Unsupervised Riemannian Clustering of Probability Density Functions. 377-392
  
• Andrew B. Goldberg, Ming Li, Xiaojin Zhu:
  Online Manifold Regularization: A New Learning Setting and Empirical Study. 393-407
  
• Steve Gregory:
  A Fast Algorithm to Find Overlapping Communities in Networks. 408-423
  
• Valerio Grossi, Andrea Romei, Salvatore Ruggieri:
  A Case Study in Sequential Pattern Mining for IT-Operational Risk. 424-439
  
• Henrik Grosskreutz, Stefan Rüping, Stefan Wrobel:
  Tight Optimistic Estimates for Fast Subgroup Discovery. 440-456
  
• Sonal Gupta, Joohyun Kim, Kristen Grauman, Raymond J. Mooney:
  Watch, Listen & Learn: Co-training on Captioned Images and Videos. 457-472
  
• Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt:
  Parameter Learning in Probabilistic Databases: A Least Squares Approach. 473-488
  
• Md. Rafiul Hassan, M. Maruf Hossain, James Bailey, Kotagiri Ramamohanarao:
  Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics. 489-504
  
• Kathryn Hempstalk, Eibe Frank, Ian H. Witten:
  One-Class Classification by Combining Density and Class Probability Estimation. 505-519
  
• Tamás Horváth, Jan Ramon:
  Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth. 520-535
  
• Jin Huang, Charles X. Ling, Harry Zhang, Stan Matwin:
  Proper Model Selection with Significance Test. 536-547
  
• Nathalie Japkowicz, Pritika Sanghi, Peter E. Tischer:
  A Projection-Based Framework for Classifier Performance Evaluation. 548-563
  
• Yangqing Jia, Zheng Wang, Changshui Zhang:
  Distortion-Free Nonlinear Dimensionality Reduction. 564-579
  
• Ata Kabán, Robert J. Durrant:
  Learning with L_q<1 vs L₁-Norm Regularisation with Exponentially Many Irrelevant Features. 580-596
  
• Kin Fai Kan, Christian R. Shelton:
  Catenary Support Vector Machines. 597-610
  
• Thoralf Klein, Ulf Brefeld, Tobias Scheffer:
  Exact and Approximate Inference for Annotating Graphs with Structural SVMs. 611-623
  
• Stanley Kok, Pedro Domingos:
  Extracting Semantic Networks from Text Via Relational Clustering. 624-639
  
• Jussi Kujala, Tapio Elomaa:
  Ranking the Uniformity of Interval Pairs. 640-655
  
• Lior Kuyer, Shimon Whiteson, Bram Bakker, Nikos A. Vlassis:
  Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs. 656-671
  
• Matthijs van Leeuwen, Arno Siebes:
  StreamKrimp: Detecting Change in Data Streams. 672-687
  

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