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Ensemble Learning

347 directly classified papers

Papers per year

Papers

Adaptive Martingale Boosting NIPS 2008
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features NIPS 2008
Boosting the Area under the ROC Curve NIPS 2007
One-Pass Boosting NIPS 2007
Boosting Algorithms for Maximizing the Soft Margin NIPS 2007
Regularized Boost for Semi-Supervised Learning NIPS 2007
Agreement-Based Learning NIPS 2007
A General Boosting Method and its Application to Learning Ranking Functions for Web Search NIPS 2007
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts JMLR 2007
Ensemble Clustering using Semidefinite Programming NIPS 2007
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions NIPS 2006
Bayesian Ensemble Learning NIPS 2006
Sparse Boosting JMLR 2006
Quantile Regression Forests JMLR 2006
Managing Diversity in Regression Ensembles JMLR 2005
Stability of Randomized Learning Algorithms JMLR 2005
Efficient Margin Maximizing with Boosting JMLR 2005
The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins JMLR 2004
Learning Ensembles from Bites: A Scalable and Accurate Approach JMLR 2004
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions JMLR 2002
Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem JMLR 2002
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers JMLR 2000