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ORCID14th PKDD / 21st ECML 2010: Barcelona, Spain
- José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag:
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I. Lecture Notes in Computer Science 6321, Springer 2010, ISBN 978-3-642-15879-7
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 A. 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 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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