Pages that link to "Item:Q1807156"

The following pages link to Boosting the margin: a new explanation for the effectiveness of voting methods (Q1807156):

Displaying 47 items.

• An algorithmic theory of learning: Robust concepts and random projection (Q2499543) (← links)
• Complexities of convex combinations and bounding the generalization error in classification (Q2583410) (← links)
• Boosting with early stopping: convergence and consistency (Q2583412) (← links)
• A novel margin based algorithm for feature extraction (Q2655576) (← links)
• Model and method for constructing a heterogeneous cluster ensemble (Q2691540) (← links)
• Attractor networks for shape recognition (Q2723314) (← links)
• Reduction from cost-sensitive ordinal ranking to weighted binary classification (Q2919409) (← links)
• Analysis of the generalization ability of a full decision tree (Q2940504) (← links)
• Measuring Impact of Diversity of Classifiers on the Accuracy of Evidential Ensemble Classifiers (Q3164000) (← links)
• Discriminative Reranking for Natural Language Parsing (Q3225425) (← links)
• Boosting with missing predictors (Q3305011) (← links)
• Theory of Classification: a Survey of Some Recent Advances (Q3373749) (← links)
• Novel Aggregate Deletion/Substitution/Addition Learning Algorithms for Recursive Partitioning (Q3391141) (← links)
• Automated trading with boosting and expert weighting (Q3564810) (← links)
• Nonparametric Modeling of Neural Point Processes via Stochastic Gradient Boosting Regression (Q3591513) (← links)
• Prototype Classification: Insights from Machine Learning (Q3612119) (← links)
• Theory and Algorithm for Learning with Dissimilarity Functions (Q3628019) (← links)
• (Q4614113) (← links)
• Aggregating classifiers with ordinal response structure (Q4675843) (← links)
• Boosting with Noisy Data: Some Views from Statistical Theory (Q4819816) (← links)
• Different Paradigms for Choosing Sequential Reweighting Algorithms (Q4819817) (← links)
• Ten More Years of Error Rate Research (Q4831978) (← links)
• Information Geometry of U-Boost and Bregman Divergence (Q4832497) (← links)
• (Q4969094) (← links)
• Superlinear Integrality Gaps for the Minimum Majority Problem (Q5020845) (← links)
• (Q5053228) (← links)
• Weighted bagging: a modification of AdaBoost from the perspective of importance sampling (Q5124773) (← links)
• Structure from Randomness in Halfspace Learning with the Zero-One Loss (Q5139592) (← links)
• Toward Computing the Margin of Victory in Single Transferable Vote Elections (Q5139621) (← links)
• (Q5149018) (← links)
• An Integrated Fuzzy Cells-Classifier (Q5306990) (← links)
• Properties of Bagged Nearest Neighbour Classifiers (Q5313456) (← links)
• Selection of Binary Variables and Classification by Boosting (Q5436402) (← links)
• Robust Loss Functions for Boosting (Q5440967) (← links)
• Deep learning: a statistical viewpoint (Q5887827) (← links)
• Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation (Q5887828) (← links)
• An iterated classification rule based on auxiliary pseudo-predictors. (Q5958221) (← links)
• Improving nonparametric regression methods by bagging and boosting. (Q5958473) (← links)
• Recent developments in bootstrap methodology (Q5965013) (← links)
• Comment (Q5965645) (← links)
• Parallel orthogonal deep neural network (Q6078756) (← links)
• Space-dependent turbulence model aggregation using machine learning (Q6119255) (← links)
• Nested cross-validation with ensemble feature selection and classification model for high-dimensional biological data (Q6171282) (← links)
• Machine collaboration (Q6548943) (← links)
• Machine Learning vs. Survival Analysis Models: a study on right censored heart failure data (Q6562743) (← links)
• Convex Bidirectional Large Margin Classifiers (Q6621634) (← links)
• A new kernel regression approach for robustified <i>L</i> ₂ boosting (Q6641333) (← links)