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ORCID16th ECML 2005: Porto, Portugal
- João Gama, Rui Camacho, Pavel Brazdil, Alípio Jorge, Luís Torgo:
Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings. Lecture Notes in Computer Science 3720, Springer 2005, ISBN 3-540-29243-8
Invited Talks
(shared with PKDD 2005)
- Michael R. Berthold:
Data Analysis in the Life Sciences - Sparking Ideas -. 1 - Claire Cardie:
Machine Learning for Natural Language Processing (and Vice Versa?). 2 - Luc De Raedt:
Statistical Relational Learning: An Inductive Logic Programming Perspective. 3-5 - Eamonn J. Keogh:
Recent Advances in Mining Time Series Data. 6 - Ron Kohavi:
Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce. 7 - Yossi Matias:
Data Streams and Data Synopses for Massive Data Sets. 8-9
Long Papers
- Liviu Badea:
Clustering and Metaclustering with Nonnegative Matrix Decompositions. 10-22 - Christian Bessiere, Remi Coletta, Frédéric Koriche, Barry O'Sullivan
:
A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems. 23-34 - Steffen Bickel, Tobias Scheffer:
Estimation of Mixture Models Using Co-EM. 35-46 - Matthew Brand:
Nonrigid Embeddings for Dimensionality Reduction. 47-59 - Ulf Brefeld, Christoph Büscher, Tobias Scheffer:
Multi-view Discriminative Sequential Learning. 60-71 - Jesús Cerquides, Ramón López de Mántaras:
Robust Bayesian Linear Classifier Ensembles. 72-83 - Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa:
An Integrated Approach to Learning Bayesian Networks of Rules. 84-95 - Isabel Drost, Tobias Scheffer:
Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam. 96-107 - Arkady Epshteyn, Gerald DeJong:
Rotational Prior Knowledge for SVMs. 108-119 - Stefano Ferilli, Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito:
On the LearnAbility of Abstraction Theories from Observations for Relational Learning. 120-132 - George Forman, Ira Cohen:
Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers. 133-145 - Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu:
Kernel Basis Pursuit. 146-157 - Iris Hendrickx, Antal van den Bosch:
Hybrid Algorithms with Instance-Based Classification. 158-169 - Aloak Kapoor, Russell Greiner:
Learning and Classifying Under Hard Budgets. 170-181 - Wolf Kienzle, Bernhard Schölkopf:
Training Support Vector Machines with Multiple Equality Constraints. 182-193 - Hans van Kuilenburg, Marco A. Wiering, Marten den Uyl:
A Model Based Method for Automatic Facial Expression Recognition. 194-205 - François Laviolette, Mario Marchand, Mohak Shah:
Margin-Sparsity Trade-Off for the Set Covering Machine. 206-217 - Xiaoli Li, Bing Liu:
Learning from Positive and Unlabeled Examples with Different Data Distributions. 218-229 - Shiau Hong Lim, Gerald DeJong:
Towards Finite-Sample Convergence of Direct Reinforcement Learning. 230-241 - Hsuan-Tien Lin, Ling Li:
Infinite Ensemble Learning with Support Vector Machines. 242-254 - Siwei Lyu:
A Kernel Between Unordered Sets of Data: The Gaussian Mixture Approach. 255-267 - Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney:
Active Learning for Probability Estimation Using Jensen-Shannon Divergence. 268-279 - Jan Peters, Sethu Vijayakumar, Stefan Schaal:
Natural Actor-Critic. 280-291 - Detlef Prescher:
Inducing Head-Driven PCFGs with Latent Heads: Refining a Tree-Bank Grammar for Parsing. 292-304 - Stefan Raeymaekers, Maurice Bruynooghe, Jan Van den Bussche:
Learning (k, l)-Contextual Tree Languages for Information Extraction. 305-316 - Martin A. Riedmiller:
Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method. 317-328 - Carsten Riggelsen:
MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition. 329-340 - Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski:
On Discriminative Joint Density Modeling. 341-352 - Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony:
Model-Based Online Learning of POMDPs. 353-364 - Shengli Sheng, Charles X. Ling, Qiang Yang:
Simple Test Strategies for Cost-Sensitive Decision Trees. 365-376 - JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin Ghahramani:
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models. 377-388 - Daniel Szer, François Charpillet:
An Optimal Best-First Search Algorithm for Solving Infinite Horizon DEC-POMDPs. 389-399 - Kari Torkkola, Eugene Tuv:
Ensemble Learning with Supervised Kernels. 400-411 - Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin:
Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. 412-424 - Ronan Trepos, Ansaf Salleb, Marie-Odile Cordier, Véronique Masson, Chantal Gascuel:
A Distance-Based Approach for Action Recommendation. 425-436 - Joannès Vermorel, Mehryar Mohri:
Multi-armed Bandit Algorithms and Empirical Evaluation. 437-448 - Gang Wang, Zhihua Zhang, Frederick H. Lochovsky:
Annealed Discriminant Analysis. 449-460 - Shijun Wang, Changshui Zhang:
Network Game and Boosting. 461-472 - Olcay Taner Yildiz, Ethem Alpaydin:
Model Selection in Omnivariate Decision Trees. 473-484 - Marie desJardins, Priyang Rathod, Lise Getoor:
Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence. 485-496
Short Papers
- Steffen Bickel, Peter Haider, Tobias Scheffer:
Learning to Complete Sentences. 497-504 - Antoine Bordes, Léon Bottou:
The Huller: A Simple and Efficient Online SVM. 505-512 - Jérôme Callut, Pierre Dupont:
Inducing Hidden Markov Models to Model Long-Term Dependencies. 513-521 - François Coste, Goulven Kerbellec:
A Similar Fragments Merging Approach to Learn Automata on Proteins. 522-529 - Chris H. Q. Ding, Xiaofeng He, Horst D. Simon:
Nonnegative Lagrangian Relaxation of K-Means and Spectral Clustering. 530-538 - Chris Drummond, Robert C. Holte:
Severe Class Imbalance: Why Better Algorithms Aren't the Answer. 539-546 - Tapio Elomaa, Jussi Kujala, Juho Rousu:
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes. 547-555 - Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe:
A Comparison of Approaches for Learning Probability Trees. 556-563 - George Forman:
Counting Positives Accurately Despite Inaccurate Classification. 564-575 - Ramunas Girdziusas, Jorma Laaksonen:
Optimal Stopping and Constraints for Diffusion Models of Signals with Discontinuities. 576-583 - Ali Hamzeh, Adel Rahmani:
An Evolutionary Function Approximation Approach to Compute Prediction in XCSF. 584-592 - Masoumeh T. Izadi, Doina Precup:
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes. 593-600 - Robin Jaulmes, Joelle Pineau, Doina Precup:
Active Learning in Partially Observable Markov Decision Processes. 601-608 - Sergio Jiménez Celorrio, Fernando Fernández, Daniel Borrajo:
Machine Learning of Plan Robustness Knowledge About Instances. 609-616 - Arnaud Lallouet, Andrei Legtchenko:
Two Contributions of Constraint Programming to Machine Learning. 617-624 - Tao Li, Wei Peng:
A Clustering Model Based on Matrix Approximation with Applications to Cluster System Log Files. 625-632 - Fletcher Lu, J. Efrim Boritz:
Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions. 633-640 - Ingo Mierswa, Michael Wurst:
Efficient Case Based Feature Construction. 641-648 - Richard Nock, Frank Nielsen:
Fitting the Smallest Enclosing Bregman Ball. 649-656 - Daniel Oblinger, Vittorio Castelli, Tessa A. Lau, Lawrence D. Bergman:
Similarity-Based Alignment and Generalization. 657-664 - Oleg Okun, Helen Priisalu, Alexessander Alves:
Fast Non-negative Dimensionality Reduction for Protein Fold Recognition. 665-672 - Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa:
Mode Directed Path Finding. 673-681 - Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi, Tu Bao Ho, Yasushi Inoguchi:
Classification with Maximum Entropy Modeling of Predictive Association Rules. 682-689 - Joaquim F. Pinto da Costa, Jaime S. Cardoso:
Classification of Ordinal Data Using Neural Networks. 690-697 - Barnabás Póczos, Bálint Takács, András Lörincz:
Independent Subspace Analysis on Innovations. 698-706 - Ricardo Rocha, Nuno A. Fonseca, Vítor Santos Costa:
On Applying Tabling to Inductive Logic Programming. 707-714 - (Withdrawn) Learning Models of Relational Stochastic Processes. 715-723
- Surendra K. Singhi, Huan Liu:
Error-Sensitive Grading for Model Combination. 724-732 - Hendrik Skubch, Michael Thielscher:
Strategy Learning for Reasoning Agents. 733-740 - Yuk Lai Suen, Prem Melville, Raymond J. Mooney:
Combining Bias and Variance Reduction Techniques for Regression Trees. 741-749 - Petroula Tsampouka, John Shawe-Taylor:
Analysis of Generic Perceptron-Like Large Margin Classifiers. 750-758 - Fang Wang, Yuhui Qiu:
Multimodal Function Optimizing by a New Hybrid Nonlinear Simplex Search and Particle Swarm Algorithm. 759-766
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