ensemble learning

Boosting the Area under the ROC Curve NeurIPS 2007 Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts JMLR 2007 Learning with Tree-Averaged Densities and Distributions NeurIPS 2007 One-Pass Boosting NeurIPS 2007 Regularized Boost for Semi-Supervised Learning NeurIPS 2007 AdaBoost is Consistent NeurIPS 2006 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006 Bayesian Ensemble Learning NeurIPS 2006 Ensemble Pruning Via Semi-definite Programming JMLR 2006 Fast Discriminative Visual Codebooks using Randomized Clustering Forests NeurIPS 2006 Multi-Instance Multi-Label Learning with Application to Scene Classification NeurIPS 2006 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NeurIPS 2006 Efficient Margin Maximizing with Boosting JMLR 2005 Managing Diversity in Regression Ensembles JMLR 2005 Learning Ensembles from Bites: A Scalable and Accurate Approach JMLR 2004 Lossless Online Bayesian Bagging JMLR 2004 Online Choice of Active Learning Algorithms JMLR 2004 Designing Committees of Models through Deliberate Weighting of Data Points JMLR 2003 Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions JMLR 2002 Round Robin Classification JMLR 2002 Shallow Parsing using Noisy and Non-Stationary Training Material JMLR 2002 Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers JMLR 2000