ensemble learning

Bayesian Classifier Combination AISTATS 2012 Context-Sensitive Decision Forests for Object Detection NeurIPS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Learning Image Descriptors with the Boosting-Trick NeurIPS 2012 ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel JMLR 2012 Multi-Target Regression with Rule Ensembles JMLR 2012 SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012 Active Boosted Learning (ActBoost) AISTATS 2011 A Machine Learning Approach to Predict Chemical Reactions NeurIPS 2011 Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers ACML 2011 Multiclass Boosting: Theory and Algorithms NeurIPS 2011 The Rate of Convergence of Adaboost COLT 2011 Two-Layer Multiple Kernel Learning AISTATS 2011 Variance Penalizing AdaBoost NeurIPS 2011 Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking ACML 2010 A Theory of Multiclass Boosting NeurIPS 2010 Error-Correcting Output Codes Library JMLR 2010 Sidestepping Intractable Inference with Structured Ensemble Cascades NeurIPS 2010 Boosting with Spatial Regularization NeurIPS 2009 Ensemble Nystrom Method NeurIPS 2009 Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models NeurIPS 2009 Adaptive Martingale Boosting NeurIPS 2008 Support Vector Machinery for Infinite Ensemble Learning JMLR 2008 Agreement-Based Learning NeurIPS 2007 Boosting Algorithms for Maximizing the Soft Margin NeurIPS 2007