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Semantic Scholar12. PKDD / 19. ECML 2008: Antwerp, Belgium
Walter Daelemans, Bart Goethals, Katharina Morik:
Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I. Lecture Notes in Computer Science 5211, Springer 2008, ISBN 978-3-540-87478-2
Invited Talks (Abstracts)
Machine Learning Journal Abstracts
- 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 - Markus Weimer, Alexandros Karatzoglou, Alexander J. Smola:
Improving Maximum Margin Matrix Factorization. 14
Data Mining and Knowledge Discovery Journal Abstracts
- Adrian Kügel, Enno Ohlebusch:
A Space Efficient Solution to the Frequent String Mining Problem for Many Databases. 16 - Apostolos N. Papadopoulos, Apostolos Lyritsis, Yannis Manolopoulos:
SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs. 18 - 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 - 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 - 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 - Giorgio Corani, Marco Zaffalon:
Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities. 257-271 - 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 Eladio 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 - 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 Lq<1 vs L1-Norm Regularisation with Exponentially Many Irrelevant Features. 580-596 - Thoralf Klein, Ulf Brefeld, Tobias Scheffer:
Exact and Approximate Inference for Annotating Graphs with Structural SVMs. 611-623 - Stanley Kok, Pedro M. Domingos:
Extracting Semantic Networks from Text Via Relational Clustering. 624-639 - Lior Kuyer, Shimon Whiteson, Bram Bakker, Nikos A. Vlassis:
Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs. 656-671
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