Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Comparison of Ensemble Approaches: Mixture of Experts and AdaBoost for a Regression Problem
Boosting Methods for Regression
Decision tree ensembles based on kernel features
An extensive empirical comparison of ensemble learning methods for binary classification
Statistical Learning from a Regression Perspective
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
Hybrid ensemble approach for classification
Bagging Predictors
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
Checkpoint Ensembles: Ensemble Methods from a Single Training Process
AdaBoost with SVM-based component classifiers
A survey on multi-output regression
A Partition-Based Framework for Building and Validating Regression Models
Boosting SVM classifiers by ensemble
Ensemble classifiers with improved overfitting
A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data
Negative Correlation Ensemble Learning for Ordinal Regression
Query Learning Strategies Using Boosting and Bagging
Algorithms for regression and classification: robust regression and genetic association studies
Extreme Learning Machine for Regression and Multiclass Classification
Two-hidden-layer extreme learning machine for regression and classification
DigitalGamesinEducation: TheDesignofGames-BasedLearning Environments
Learning Nonlinear Spectral Filters for Color Image Reconstruction
Occlusal Plane Determination Using Custom Made Broadrick Occlusal Plane Analyser: A Case Control Study
Profiling of N-glycosylation gene expression in CHO cell fed-batch cultures.
Additive Logistic Regression: a Statistical View of Boosting