17. ECML 2006: Berlin, Germany
Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (Eds.): Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings. Springer 2006 Lecture Notes in Computer Science ISBN 3-540-45375-X
Invited Talks
- Charu C. Aggarwal: On Temporal Evolution in Data Streams. ... 1
- C. Lee Giles: The Future of CiteSeer: CiteSeerx. ... 2
- Jonathan Schaeffer: Learning to Have Fun. ... 3
- Sebastian Thrun: Winning the DARPA Grand Challenge. ... 4
- Henry Tirri: Challenges of Urban Sensing. ... 5
Long Papers
- Alon Altman, Avivit Bercovici-Boden, Moshe Tennenholtz: Learning in One-Shot Strategic Form Games. 6-17
- Massih-Reza Amini, Nicolas Usunier, François Laviolette, Alexandre Lacasse, Patrick Gallinari: A Selective Sampling Strategy for Label Ranking. 18-29
- Christopher H. Bryant, Daniel Fredouille, Alex Wilson, Channa K. Jayawickreme, Steven Jupe, Simon Topp: Pertinent Background Knowledge for Learning Protein Grammars. 54-65
- John Burge, Terran Lane: Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies. 66-77
- Alexander Clark, Christophe Costa Florêncio, Chris Watkins: Languages as Hyperplanes: Grammatical Inference with String Kernels. 90-101
- Gerald DeJong: Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning. 102-113
- William Elazmeh, Nathalie Japkowicz, Stan Matwin: Evaluating Misclassifications in Imbalanced Data. 126-137
- Raquel Fuentetaja, Daniel Borrajo: Improving Control-Knowledge Acquisition for Planning by Active Learning. 138-149
- Ricard Gavaldà, Philipp W. Keller, Joelle Pineau, Doina Precup: PAC-Learning of Markov Models with Hidden State. 150-161
- David Grangier, Florent Monay, Samy Bengio: A Discriminative Approach for the Retrieval of Images from Text Queries. 162-173
- Bernd Gutmann, Kristian Kersting: TildeCRF: Conditional Random Fields for Logical Sequences. 174-185
- Corneliu Henegar, Karine Clément, Jean-Daniel Zucker: Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data. 186-197
- Sébastien Jodogne, Cyril Briquet, Justus H. Piater: Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks. 210-221
- Sébastien Jodogne, Justus H. Piater: Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions. 222-233
- Nathaniel J. King, Neil D. Lawrence: Fast Variational Inference for Gaussian Process Models Through KL-Correction. 270-281
- Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun: Transductive Gaussian Process Regression with Automatic Model Selection. 306-317
- Alessandro Moschitti: Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees. 318-329
- Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bratko: Why Is Rule Learning Optimistic and How to Correct It. 330-340
- Tobias Pfingsten: Bayesian Active Learning for Sensitivity Analysis. 353-364
- Martin Scholz: Boosting in PN Spaces. 377-388
- Hyunjung Shin, N. Jeremy Hill, Gunnar Rätsch: Graph Based Semi-supervised Learning with Sharper Edges. 401-412
- Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin: Skill Acquisition Via Transfer Learning and Advice Taking. 425-436
- Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao: Batch Classification with Applications in Computer Aided Diagnosis. 449-460
- Michael Wurst, Katharina Morik, Ingo Mierswa: Localized Alternative Cluster Ensembles for Collaborative Structuring. 485-496
- Bojun Yan, Carlotta Domeniconi: Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data. 509-520
- Ying Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting: To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles. 533-544
Short Papers
- Will Bridewell, Pat Langley, Steve Racunas, Stuart R. Borrett: Learning Process Models with Missing Data. 557-565
- Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet: Cascade Evaluation of Clustering Algorithms. 574-581
- Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Ying Ma: Fast Spectral Clustering of Data Using Sequential Matrix Compression. 590-597
- Antonio D. Chiaravalloti, Gianluigi Greco, Antonella Guzzo, Luigi Pontieri: An Information-Theoretic Framework for High-Order Co-clustering of Heterogeneous Objects. 598-605
- Trevor Cohn: Efficient Inference in Large Conditional Random Fields. 606-613
- Juan C. Cuevas-Tello, Peter Tiño, Somak Raychaudhury: A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses. 614-621
- Jason V. Davis, Jungwoo Ha, Christopher J. Rossbach, Hany E. Ramadan, Emmett Witchel: Cost-Sensitive Decision Tree Learning for Forensic Classification. 622-629
- Alexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington: The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces. 630-637
- Peter Geibel: Reinforcement Learning for MDPs with Constraints. 646-653
- Faustino J. Gomez, Jürgen Schmidhuber, Risto Miikkulainen: Efficient Non-linear Control Through Neuroevolution. 654-662
- Derek Greene, Padraig Cunningham: Efficient Prediction-Based Validation for Document Clustering. 663-670
- Manfred Jaeger: On Testing the Missing at Random Assumption. 671-678
- Georgi I. Nalbantov, Jan C. Bioch, Patrick J. F. Groenen: Classification with Support Hyperplanes. 703-710
- Kee Siong Ng: (Agnostic) PAC Learning Concepts in Higher-Order Logic. 711-718
- Roland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér: Evaluating Feature Selection for SVMs in High Dimensions. 719-726
- Martin Nyffenegger, Jean-Cédric Chappelier, Éric Gaussier: Revisiting Fisher Kernels for Document Similarities. 727-734
- Scott Proper, Prasad Tadepalli: Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery. 735-742
- Stefan Rüping: Robust Probabilistic Calibration. 743-750
- Péter Schönhofen, András A. Benczúr: Exploiting Extremely Rare Features in Text Categorization. 759-766
- Suvrit Sra: Efficient Large Scale Linear Programming Support Vector Machines. 767-774
- Jan Struyf, Jesse Davis, C. David Page Jr.: An Efficient Approximation to Lookahead in Relational Learners. 775-782
- Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani: Improvement of Systems Management Policies Using Hybrid Reinforcement Learning. 783-791
- Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham: Dynamic Integration with Random Forests. 801-808
- Samuel Wieczorek, Gilles Bisson, Mirta B. Gordon: Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption Test. 817-824
- Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang: Spline Embedding for Nonlinear Dimensionality Reduction. 825-832
- Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel: Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures. 841-848
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last updated on 2013-06-18T211851 by the dblp team