Boosting First-Order Learning

Soft Margins for AdaBoost

Machine Learning

Logical analysis of data with decomposable structures

Theoretical Computer Science

Scaling Boosting by Margin-Based Inclusionof Features and Relations

ECML '02 Proceedings of the 13th European Conference on Machine Learning

Learning First Order Logic Time Series Classifiers: Rules and Boosting

PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery

Proof Length as an Uncertainty Factor in ILP

Soft-Ware 2002 Proceedings of the First International Conference on Computing in an Imperfect World

Robust Ensemble Learning for Data Mining

PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications

Combining Multiclass Maximum Entropy Text Classifiers with Neural Network Voting

PorTAL '02 Proceedings of the Third International Conference on Advances in Natural Language Processing

Relational Learning Using Constrained Confidence-Rated Boosting

ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming

Resampling vs Reweighting in Boosting a Relational Weak Learner

AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence

Maximizing the Margin with Boosting

COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory

An Unsupervised Collaborative Learning Method to Refine Classification Hierarchies

ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence

An introduction to boosting and leveraging

Advanced lectures on machine learning

Collaborative multi-strategy classification: application to per-pixel analysis of images

MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data

First order random forests: Learning relational classifiers with complex aggregates

Machine Learning

Collaborative multi-step mono-level multi-strategy classification

Multimedia Tools and Applications

Boosting Descriptive ILP for Predictive Learning in Bioinformatics

Inductive Logic Programming

Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble

ECML '07 Proceedings of the 18th European conference on Machine Learning

Supervised projection approach for boosting classifiers

Pattern Recognition

The graph neural network model

IEEE Transactions on Neural Networks

Averaged boosting: a noise-robust ensemble method

PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining

An empirical evaluation of bagging in inductive logic programming

ILP'02 Proceedings of the 12th international conference on Inductive logic programming

Seeing the forest through the trees: learning a comprehensible model from a first order ensemble

ILP'07 Proceedings of the 17th international conference on Inductive logic programming

An integrated approach to learning bayesian networks of rules

ECML'05 Proceedings of the 16th European conference on Machine Learning

Modelling metabolic pathways using stochastic logic programs-based ensemble methods

CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology

Dietary patterns analysis using data mining method. An application to data from the CYKIDS study

Computer Methods and Programs in Biomedicine