14. PKDD / 21. ECML 2010: Barcelona, Spain

Invited Talks (Abstracts)

• Christos Faloutsos:
  Mining Billion-Node Graphs: Patterns, Generators and Tools. 1
  
• Jiawei Han:
  Structure Is Informative: On Mining Structured Information Networks. 2
  
• Leslie Pack Kaelbling:
  Intelligent Interaction with the Real World. 3
  
• Hod Lipson:
  Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology. 4
  
• Tomaso Poggio:
  Hierarchical Learning Machines and Neuroscience of Visual Cortex. 5
  
• Jürgen Schmidhuber:
  Formal Theory of Fun and Creativity. 6
  

Regular Papers

• Marco Aldinucci, Salvatore Ruggieri, Massimo Torquati:
  Porting Decision Tree Algorithms to Multicore Using FastFlow. 7-23
  
• Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi:
  On Classifying Drifting Concepts in P2P Networks. 24-39
  
• Josh Attenberg, Prem Melville, Foster J. Provost:
  A Unified Approach to Active Dual Supervision for Labeling Features and Examples. 40-55
  
• Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessandro Verri:
  Vector Field Learning via Spectral Filtering. 56-71
  
• Cécile Barat, Christophe Ducottet, Élisa Fromont, Anne-Claire Legrand, Marc Sebban:
  Weighted Symbols-Based Edit Distance for String-Structured Image Classification. 72-86
  
• Iyad Batal, Milos Hauskrecht:
  A Concise Representation of Association Rules Using Minimal Predictive Rules. 87-102
  
• François Bavaud:
  Euclidean Distances, Soft and Spectral Clustering on Weighted Graphs. 103-118
  
• Eva Besada-Portas, Sergey M. Plis, Jesús Manuel de la Cruz, Terran Lane:
  Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks. 119-134
  
• Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer:
  Leveraging Bagging for Evolving Data Streams. 135-150
  
• Christian Böhm, Frank Fiedler, Annahita Oswald, Claudia Plant, Bianca Wackersreuther, Peter Wackersreuther:
  ITCH: Information-Theoretic Cluster Hierarchies. 151-167
  
• Ilaria Bordino, Debora Donato, Ricardo A. Baeza-Yates:
  Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis. 168-183
  
• Josep Carmona, Jordi Cortadella:
  Process Mining Meets Abstract Interpretation. 184-199
  
• Pablo Samuel Castro, Doina Precup:
  Smarter Sampling in Model-Based Bayesian Reinforcement Learning. 200-214
  
• Weiwei Cheng, Michaël Rademaker, Bernard De Baets, Eyke Hüllermeier:
  Predicting Partial Orders: Ranking with Abstention. 215-230
  
• Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong, Gary Kee Khoon Lee:
  Predictive Distribution Matching SVM for Multi-domain Learning. 231-247
  
• Stéphan Clémençon, Jérémie Jakubowicz:
  Kantorovich Distances between Rankings with Applications to Rank Aggregation. 248-263
  
• Somayeh Danafar, Arthur Gretton, Jürgen Schmidhuber:
  Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition. 264-279
  
• Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier:
  Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss. 280-295
  
• Gerben de Vries, Maarten van Someren:
  Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression. 296-311
  
• Dotan Di Castro, Shie Mannor:
  Adaptive Bases for Reinforcement Learning. 312-327
  
• Tom Diethe, David R. Hardoon, John Shawe-Taylor:
  Constructing Nonlinear Discriminants from Multiple Data Views. 328-343
  
• Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lise Getoor:
  Learning Algorithms for Link Prediction Based on Chance Constraints. 344-360
  
• Wenjun Dou, Guang Dai, Congfu Xu, Zhihua Zhang:
  Sparse Unsupervised Dimensionality Reduction Algorithms. 361-376
  
• Jun Du, Charles X. Ling:
  Asking Generalized Queries to Ambiguous Oracle. 377-392
  
• Nan Du, Hao Wang, Christos Faloutsos:
  Analysis of Large Multi-modal Social Networks: Patterns and a Generator. 393-408
  
• Avinava Dubey, Indrajit Bhattacharya, Shantanu Godbole:
  A Cluster-Level Semi-supervision Model for Interactive Clustering. 409-424
  
• Frank Eichinger, Klaus Krogmann, Roland Klug, Klemens Böhm:
  Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs. 425-441
  
• Nicola Fanizzi, Claudia d'Amato, Floriana Esposito:
  Induction of Concepts in Web Ontologies through Terminological Decision Trees. 442-457
  
• Jochen Garcke:
  Classification with Sums of Separable Functions. 458-473
  
• Hirotaka Hachiya, Masashi Sugiyama:
  Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information. 474-489
  
• Blaise Hanczar, Mohamed Nadif:
  Bagging for Biclustering: Application to Microarray Data. 490-505
  
• José Miguel Hernández-Lobato, Tjeerd Dijkstra:
  Hub Gene Selection Methods for the Reconstruction of Transcription Networks. 506-521
  
• Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Thibault Helleputte, Pierre Dupont:
  Expectation Propagation for Bayesian Multi-task Feature Selection. 522-537
  
• Ilkka Huopaniemi, Tommi Suvitaival, Matej Oresic, Samuel Kaski:
  Graphical Multi-way Models. 538-553
  
• Zakria Hussain, Alex Po Leung, Kitsuchart Pasupa, David R. Hardoon, Peter Auer, John Shawe-Taylor:
  Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. 554-569
  
• Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han, Jing Gao:
  Graph Regularized Transductive Classification on Heterogeneous Information Networks. 570-586
  
• Xiaoqian Jiang, Bing Dong, Latanya Sweeney:
  Temporal Maximum Margin Markov Network. 587-600
  
• Tobias Jung, Peter Stone:
  Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration. 601-616
  

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