ECML-PKDD 2004

56 papers

A Boosting Approach to Multiple Instance Learning Peter Auer, Ronald Ortner

Adaptive Online Time Allocation to Search Algorithms Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber

An Analysis of Stopping and Filtering Criteria for Rule Learning Johannes Fürnkranz, Peter A. Flach

An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk Han Liu, Xiaobin Yuan, Qianying Tang, Rafal Kustra

An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games Avi Bab, Ronen I. Brafman

An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes Xiang Zhang, Bernd Kuhlenkötter, Klaus Kneupner

Analyzing Multi-Agent Reinforcement Learning Using Evolutionary Dynamics Pieter Jan't Hoen, Karl Tuyls

Analyzing Sensory Data Using Non-Linear Preference Learning with Feature Subset Selection Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde

Applying Support Vector Machines to Imbalanced Datasets Rehan Akbani, Stephen Kwek, Nathalie Japkowicz

Associative Clustering Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Samuel Kaski

Batch Reinforcement Learning with State Importance Lihong Li, Vadim Bulitko, Russell Greiner

Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data Shiliang Sun, Changshui Zhang, Guoqiang Yu, Naijiang Lu, Fei Xiao

Breaking Through the Syntax Barrier: Searching with Entities and Relations Soumen Chakrabarti

Cluster-Grouping: From Subgroup Discovery to Clustering Albrecht Zimmermann, Luc De Raedt

Concept Formation in Expressive Description Logics Nicola Fanizzi, Luigi Iannone, Ignazio Palmisano, Giovanni Semeraro

Conditional Independence Trees Harry Zhang, Jiang Su

Constructive Induction for Classifying Time Series Mohammed Waleed Kadous, Claude Sammut

Convergence and Divergence in Standard and Averaging Reinforcement Learning Marco A. Wiering

Data Privacy Rakesh Agrawal

Document Representation for One-Class SVM Xiaoyun Wu, Rohini K. Srihari, Zhaohui Zheng

Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework Jangmin O, Jae Won Lee, Jongwoo Lee, Byoung-Tak Zhang

Effective Voting of Heterogeneous Classifiers Grigorios Tsoumakas, Ioannis Katakis, Ioannis P. Vlahavas

Efficient Hyperkernel Learning Using Second-Order Cone Programming Ivor W. Tsang, James T. Kwok

Estimating Attributed Central Orders: An Empirical Comparison Toshihiro Kamishima, Hideto Kazawa, Shotaro Akaho

Experiments in Value Function Approximation with Sparse Support Vector Regression Tobias Jung, Thomas Uthmann

Explicit Local Models: Towards "Optimal" Optimization Algorithms Jan Poland

Exploiting Unlabeled Data in Content-Based Image Retrieval Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang

Feature Selection Filters Based on the Permutation Test Predrag Radivojac, Zoran Obradovic, A. Keith Dunker, Slobodan Vucetic

Filtered Reinforcement Learning Douglas Aberdeen

Fisher Kernels for Logical Sequences Kristian Kersting, Thomas Gärtner

Improving Progressive Sampling via Meta-Learning on Learning Curves Rui Leite, Pavel Brazdil

Improving Random Forests Marko Robnik-Sikonja

Inducing Polynomial Equations for Regression Ljupco Todorovski, Peter Ljubic, Saso Dzeroski

Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services Andreas Heß, Nicholas Kushmerick

Justification-Based Selection of Training Examples for Case Base Reduction Santiago Ontañón, Enric Plaza

Learning from Message Pairs for Automatic Email Answering Steffen Bickel, Tobias Scheffer

Learning to Fly Simple and Robust Dorian Suc, Ivan Bratko, Claude Sammut

Margin Maximizing Discriminant Analysis András Kocsor, Kornél Kovács, Csaba Szepesvári

Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees Kai Ming Ting

Methods for Rule Conflict Resolution Tony Lindgren

Model Approximation for HEXQ Hierarchical Reinforcement Learning Bernhard Hengst

Multi-Level Boundary Classification for Information Extraction Aidan Finn, Nicholas Kushmerick

Multi-Objective Classification with Info-Fuzzy Networks Mark Last

Naive Bayesian Classifiers for Ranking Harry Zhang, Jiang Su

Population Diversity in Permutation-Based Genetic Algorithm Kenny Qili Zhu, Ziwei Liu

Random Matrices in Data Analysis Dimitris Achlioptas

Real-World Learning with Markov Logic Networks Pedro M. Domingos

Sensitivity Analysis of the Result in Binary Decision Trees Isabelle Alvarez

Simultaneous Concept Learning of Fuzzy Rules Jacobus van Zyl, Ian Cloete

Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning Bohdana Ratitch, Doina Precup

Strength in Diversity: The Advance of Data Analysis David J. Hand

SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data Rong Jin, Huan Liu

The Enron Corpus: A New Dataset for Email Classification Research Bryan Klimt, Yiming Yang

The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering Marco Saerens, François Fouss, Luh Yen, Pierre Dupont

Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers Satoshi Oyama, Christopher D. Manning

Using String Kernels to Identify Famous Performers from Their Playing Style Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer