ECML-PKDD 2005

71 papers

A Clustering Model Based on Matrix Approximation with Applications to Cluster System Log Files Tao Li, Wei Peng

A Comparison of Approaches for Learning Probability Trees Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe

A Distance-Based Approach for Action Recommendation Ronan Trepos, Ansaf Salleb, Marie-Odile Cordier, Véronique Masson, Chantal Gascuel

A Kernel Between Unordered Sets of Data: The Gaussian Mixture Approach Siwei Lyu

A Model Based Method for Automatic Facial Expression Recognition Hans van Kuilenburg, Marco A. Wiering, Marten den Uyl

A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems Christian Bessiere, Remi Coletta, Frédéric Koriche, Barry O'Sullivan

A Similar Fragments Merging Approach to Learn Automata on Proteins François Coste, Goulven Kerbellec

Active Learning for Probability Estimation Using Jensen-Shannon Divergence Prem Melville, Stewart M. Yang, Maytal Saar-Tsechansky, Raymond J. Mooney

Active Learning in Partially Observable Markov Decision Processes Robin Jaulmes, Joelle Pineau, Doina Precup

An Evolutionary Function Approximation Approach to Compute Prediction in XCSF Ali Hamzeh, Adel Rahmani

An Integrated Approach to Learning Bayesian Networks of Rules Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa

An Optimal Best-First Search Algorithm for Solving Infinite Horizon DEC-POMDPs Daniel Szer, François Charpillet

Analysis of Generic Perceptron-like Large Margin Classifiers Petroula Tsampouka, John Shawe-Taylor

Annealed Discriminant Analysis Gang Wang, Zhihua Zhang, Frederick H. Lochovsky

Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes Tapio Elomaa, Jussi Kujala, Juho Rousu

Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence Marie desJardins, Priyang Rathod, Lise Getoor

Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers George Forman, Ira Cohen

Classification of Ordinal Data Using Neural Networks Joaquim F. Pinto da Costa, Jaime S. Cardoso

Classification with Maximum Entropy Modeling of Predictive Association Rules Xuan Hieu Phan, Minh Le Nguyen, Susumu Horiguchi, Tu Bao Ho, Yasushi Inoguchi

Clustering and Metaclustering with Nonnegative Matrix Decompositions Liviu Badea

Combining Bias and Variance Reduction Techniques for Regression Trees Yuk Lai Suen, Prem Melville, Raymond J. Mooney

Counting Positives Accurately Despite Inaccurate Classification George Forman

Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions Fletcher Lu, J. Efrim Boritz

Efficient Case Based Feature Construction Ingo Mierswa, Michael Wurst

Ensemble Learning with Supervised Kernels Kari Torkkola, Eugene Tuv

Error-Sensitive Grading for Model Combination Surendra K. Singhi, Huan Liu

Estimation of Mixture Models Using Co-EM Steffen Bickel, Tobias Scheffer

Fast Non-Negative Dimensionality Reduction for Protein Fold Recognition Oleg Okun, Helen Priisalu, Alexessander Alves

Fitting the Smallest Enclosing Bregman Ball Richard Nock, Frank Nielsen

Hybrid Algorithms with Instance-Based Classification Iris Hendrickx, Antal van den Bosch

Independent Subspace Analysis on Innovations Barnabás Póczos, Bálint Takács, András Lörincz

Inducing Head-Driven PCFGs with Latent Heads: Refining a Tree-Bank Grammar for Parsing Detlef Prescher

Inducing Hidden Markov Models to Model Long-Term Dependencies Jérôme Callut, Pierre Dupont

Infinite Ensemble Learning with Support Vector Machines Hsuan-Tien Lin, Ling Li

Kernel Basis Pursuit Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu

Learning (k, L)-Contextual Tree Languages for Information Extraction Stefan Raeymaekers, Maurice Bruynooghe, Jan Van den Bussche

Learning and Classifying Under Hard Budgets Aloak Kapoor, Russell Greiner

Learning from Positive and Unlabeled Examples with Different Data Distributions Xiaoli Li, Bing Liu

Learning to Complete Sentences Steffen Bickel, Peter Haider, Tobias Scheffer

Machine Learning of Plan Robustness Knowledge About Instances Sergio Jiménez Celorrio, Fernando Fernández, Daniel Borrajo

Margin-Sparsity Trade-Off for the Set Covering Machine François Laviolette, Mario Marchand, Mohak Shah

MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition Carsten Riggelsen

Mode Directed Path Finding Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa

Model Selection in Omnivariate Decision Trees Olcay Taner Yildiz, Ethem Alpaydin

Model-Based Online Learning of POMDPs Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony

Multi-Armed Bandit Algorithms and Empirical Evaluation Joannès Vermorel, Mehryar Mohri

Multi-View Discriminative Sequential Learning Ulf Brefeld, Christoph Büscher, Tobias Scheffer

Multimodal Function Optimizing by a New Hybrid Nonlinear Simplex Search and Particle Swarm Algorithm Fang Wang, Yuhui Qiu

Natural Actor-Critic Jan Peters, Sethu Vijayakumar, Stefan Schaal

Network Game and Boosting Shijun Wang, Changshui Zhang

Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method Martin A. Riedmiller

Nonnegative Lagrangian Relaxation of K-Means and Spectral Clustering Chris H. Q. Ding, Xiaofeng He, Horst D. Simon

Nonrigid Embeddings for Dimensionality Reduction Matthew Brand

On Applying Tabling to Inductive Logic Programming Ricardo Rocha, Nuno A. Fonseca, Vítor Santos Costa

On Discriminative Joint Density Modeling Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski

On the LearnAbility of Abstraction Theories from Observations for Relational Learning Stefano Ferilli, Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito

Optimal Stopping and Constraints for Diffusion Models of Signals with Discontinuities Ramunas Girdziusas, Jorma Laaksonen

Robust Bayesian Linear Classifier Ensembles Jesús Cerquides, Ramón López de Mántaras

Rotational Prior Knowledge for SVMs Arkady Epshteyn, Gerald DeJong

Severe Class Imbalance: Why Better Algorithms Aren't the Answer Chris Drummond, Robert C. Holte

Similarity-Based Alignment and Generalization Daniel Oblinger, Vittorio Castelli, Tessa A. Lau, Lawrence D. Bergman

Simple Test Strategies for Cost-Sensitive Decision Trees Shengli Sheng, Charles X. Ling, Qiang Yang

Strategy Learning for Reasoning Agents Hendrik Skubch, Michael Thielscher

The Huller: A Simple and Efficient Online SVM Antoine Bordes, Léon Bottou

Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam Isabel Drost, Tobias Scheffer

Towards Finite-Sample Convergence of Direct Reinforcement Learning Shiau Hong Lim, Gerald DeJong

Training Support Vector Machines with Multiple Equality Constraints Wolf Kienzle, Bernhard Schölkopf

Two Contributions of Constraint Programming to Machine Learning Arnaud Lallouet, Andrei Legtchenko

U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin Ghahramani

Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richard Maclin

Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes Masoumeh T. Izadi, Doina Precup