← Learning Types
Machine Learning › Learning Types ›

Ensemble Learning

347 directly classified papers

Papers per year

Papers

Fast Object Detection with Entropy-Driven Evaluation CVPR 2013
Decision Jungles: Compact and Rich Models for Classification NIPS 2013
Human Boosting ICML 2013
PDM-ENLOR: Learning Ensemble of Local PDM-Based Regressions CVPR 2013
Open Problem: Lower bounds for Boosting with Hadamard Matrices COLT 2013
Ranking Forests JMLR 2013
Collaborative Active Learning of a Kernel Machine Ensemble for Recognition ICCV 2013
Direct 0-1 Loss Minimization and Margin Maximization with Boosting NIPS 2013
Reservoir Boosting : Between Online and Offline Ensemble Learning NIPS 2013
Ensemble weighted kernel estimators for multivariate entropy estimation NIPS 2012
Active Classification based on Value of Classifier NIPS 2011
The Rate of Convergence of Adaboost COLT 2011
Boosting with Maximum Adaptive Sampling NIPS 2011
A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin JMLR 2011
Machine Learning Markets AISTATS 2011
Variance Penalizing AdaBoost NIPS 2011
A Machine Learning Approach to Predict Chemical Reactions NIPS 2011
Robust Clustering as Ensembles of Affinity Relations NIPS 2010
Sidestepping Intractable Inference with Structured Ensemble Cascades NIPS 2010
Empirical Bernstein Boosting AISTATS 2010
A Theory of Multiclass Boosting NIPS 2010
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NIPS 2009
Potential-Based Agnostic Boosting NIPS 2009
Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models NIPS 2009
Boosting with Spatial Regularization NIPS 2009