ECML-PKDD 2003

53 papers

A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes Ricardo Vilalta, Irina Rish

A Generative Model for Semantic Role Labeling Cynthia A. Thompson, Roger Levy, Christopher D. Manning

A Hybrid Language Model Based on Stochastic Context-Free Grammars Diego Linares, José-Miguel Benedí, Joan-Andreu Sánchez

A Markov Network Based Factorized Distribution Algorithm for Optimization Roberto Santana

A Minimum Descriptipn Length Approach to Grammar Inference Peter Grünwald

A New Pairwise Ensemble Approach for Text Classification Yan Liu, Jaime G. Carbonell, Rong Jin

A New Way to Introduce Knowledge into Reinforcement Learning Pascal Garcia

A Two-Level Learning Method for Generalized Multi-Instance Problems Nils B. Weidmann, Eibe Frank, Bernhard Pfahringer

Abalearn: A Risk-Sensitive Approach to Self-Play Learning in Abalone Pedro F. Campos, Thibault Langlois

Backoff Parameter Estimation for the DOP Model Khalil Sima'an, Luciano Buratto

Classification Approach Towards Banking and Sorting Problems Shyamsundar Rajaram, Ashutosh Garg, Xiang Sean Zhou, Thomas S. Huang

Clustering in Knowledge Embedded Space Yungang Zhang, Changshui Zhang, Shijun Wang

COllective INtelligence with Sequences of Actions - Coordinating Actions in Multi-Agent Systems Pieter Jan't Hoen, Sander M. Bohté

Color Image Segmentation: Kernel Do the Feature Space Jianguo Lee, Jingdong Wang, Changshui Zhang

Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language Walter Daelemans, Véronique Hoste, Fien De Meulder, Bart Naudts

Could Active Perception Aid Navigation of Partially Observable Grid Worlds? Paul A. Crook, Gillian Hayes

Ensembles of Multi-Instance Learners Zhi-Hua Zhou, Min-Ling Zhang

Evaluation of Topographic Clustering and Its Kernelization Marie-Jeanne Lesot, Florence d'Alché-Buc, George Siolas

Experiments with Cost-Sensitive Feature Evaluation Marko Robnik-Sikonja

Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-Agent Systems Karl Tuyls, Dries Heytens, Ann Nowé, Bernard Manderick

From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge Pieter W. Adriaans

Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference Amaury Habrard, Marc Bernard, Marc Sebban

Improving Numerical Prediction with Qualitative Constraints Dorian Suc, Ivan Bratko

Improving Rocchio with Weakly Supervised Clustering Romain Vinot, François Yvon

Improving SVM Text Classification Performance Through Threshold Adjustment James G. Shanahan, Norbert Roma

Improving the AUC of Probabilistic Estimation Trees César Ferri, Peter A. Flach, José Hernández-Orallo

Incremental Learning of Context Free Grammars by Extended Inductive CYK Algorithm Katsuhiko Nakamura

Inference of a Subclass of Context Free Grammars Using Positive Samples J. A. Laxminarayana, G. Nagaraja

Iteratively Extending Time Horizon Reinforcement Learning Damien Ernst, Pierre Geurts, Louis Wehenkel

Learning Context Free Grammars in the Limit Aided by the Sample Distribution Yoav Seginer

Learning Rules to Improve a Machine Translation System David Kauchak, Charles Elkan

Left Aligned Grammars - Identifying a Class of Context-Free Grammar in the Limit from Positive Data Bradford Starkie

Leveraging Lexical Semantics to Infer Context-Free Grammars Tim Oates, Tom Armstrong, Justin Harris, Mark Nejman

Life Cycle Modeling of News Events Using Aging Theory Chien Chin Chen, Yao-Tsung Chen, Yeali S. Sun, Meng Chang Chen

Logistic Model Trees Niels Landwehr, Mark Hall, Eibe Frank

Next Generation Data Mining Tools: Power Laws and Self-Similarity for Graphs, Streams and Traditional Data Christos Faloutsos

Offspring-Annotated Probabilistic Context-Free Grammars Jose L. Verdú-Mas, Jorge Calera-Rubio, Rafael C. Carrasco

On Boosting Improvement: Error Reduction and Convergence Speed-up Marc Sebban, Henri-Maxime Suchier

Optimising Performance of Competing Search Engines in Heterogeneous Web Environments Rinat Khoussainov, Nicholas Kushmerick

Optimizing Local Probability Models for Statistical Parsing Kristina Toutanova, Mark Mitchell, Christopher D. Manning

Pairwise Preference Learning and Ranking Johannes Fürnkranz, Eyke Hüllermeier

Rademacher Penalization over Decision Tree Prunings Matti Kääriäinen, Tapio Elomaa

Robust K-DNF Learning via Inductive Belief Merging Frédéric Koriche, Joël Quinqueton

Scaled CGEM: A Fast Accelerated EM Jörg Fischer, Kristian Kersting

Self-Evaluated Learning Agent in Multiple State Games Koichi Moriyama, Masayuki Numao

Support Vector Machines with Example Dependent Costs Ulf Brefeld, Peter Geibel, Fritz Wysotzki

Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions Donald B. Rubin

Two-Eyed Algorithms and Problems Leo Breiman

Unambiguous Automata Inference by Means of State-Merging Methods François Coste, Daniel Fredouille

Unsupervised Grammar Induction in a Framework of Information Compression by Multiple Alignment, Unification and Search J. Gerard Wolff

Using MDP Characteristics to Guide Exploration in Reinforcement Learning Bohdana Ratitch, Doina Precup

Visualizations for Assessing Convergence and Mixing of MCMC Jarkko Venna, Samuel Kaski, Jaakko Peltonen

Volume Under the ROC Surface for Multi-Class Problems César Ferri, José Hernández-Orallo, Miguel A. Salido