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Ensemble Pruning

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Showing 1–27 of 27 papers

TitleStatusHype
LLM-TOPLA: Efficient LLM Ensemble by Maximising DiversityCode0
Robust Few-Shot Ensemble Learning with Focal Diversity-Based PruningCode0
Liquid Democracy for Low-Cost Ensemble Pruning—0
Hierarchical Pruning of Deep Ensembles with Focal DiversityCode0
Autoselection of the Ensemble of Convolutional Neural Networks with Second-Order Cone ProgrammingCode0
A Robust Hypothesis Test for Tree Ensemble Pruning—0
Ensemble pruning via an integer programming approach with diversity constraints—0
The Shapley Value in Machine LearningCode1
Boosting Deep Ensemble Performance with Hierarchical PruningCode0
Conceptually Diverse Base Model Selection for Meta-Learners in Concept Drifting Data StreamsCode0
Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-RefinementCode0
Learn Together, Stop Apart: a Novel Approach to Ensemble Pruning—0
On-the-Fly Ensemble Pruning in Evolving Data Streams—0
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity MetricsCode0
The Shapley Value of Classifiers in Ensemble GamesCode1
When does Diversity Help Generalization in Classification Ensembles?—0
Sub-Architecture Ensemble Pruning in Neural Architecture SearchCode0
Ensemble Pruning via Margin Maximization—0
The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction—0
Ensemble Pruning based on Objection Maximization with a General Distributed FrameworkCode0
Evolving Ensemble Fuzzy Classifier—0
Personalized Classifier Ensemble Pruning Framework for Mobile Crowdsourcing—0
Random Forest Based Approach for Concept Drift Handling—0
Optimally Pruning Decision Tree Ensembles With Feature Cost—0
An Outlier Detection-based Tree Selection Approach to Extreme Pruning of Random Forests—0
On Extreme Pruning of Random Forest Ensembles for Real-time Predictive Applications—0
Learning to Diversify via Weighted Kernels for Classifier Ensemble—0
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