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Ensemble Learning

98 directly classified papers

Papers per year

Papers

A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors ACML 2017
Logistic Boosting Regression for Label Distribution Learning CVPR 2016
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles NIPS 2016
Oriented Edge Forests for Boundary Detection CVPR 2015
Learning to Propose Objects CVPR 2015
Do we Need Hundreds of Classifiers to Solve Real World Classification Problems? JMLR 2014
Ensemble Learning for Confidence Measures in Stereo Vision CVPR 2013
Human Pose Estimation Using Body Parts Dependent Joint Regressors CVPR 2013
Reservoir Boosting : Between Online and Offline Ensemble Learning NIPS 2013
Collaborative Active Learning of a Kernel Machine Ensemble for Recognition ICCV 2013
GeoF: Geodesic Forests for Learning Coupled Predictors CVPR 2013
On Using Nearly-Independent Feature Families for High Precision and Confidence ACML 2012
ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel JMLR 2012
Multiclass Boosting: Theory and Algorithms NIPS 2011
The Fast Convergence of Boosting NIPS 2011
Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers ACML 2011
Joint Cascade Optimization Using A Product Of Boosted Classifiers NIPS 2010
Potential-Based Agnostic Boosting NIPS 2009
Ensemble Nystrom Method NIPS 2009
PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning NIPS 2008
Boosting Algorithms for Maximizing the Soft Margin NIPS 2007
Regularized Boost for Semi-Supervised Learning NIPS 2007
One-Pass Boosting NIPS 2007