The following pages link to (Q3174158):
Displaying 23 items.
- A simple extension of boosting for asymmetric mislabeled data (Q419240) (← links)
- Boosting algorithms: regularization, prediction and model fitting (Q449780) (← links)
- Collective-agreement-based pruning of ensembles (Q961226) (← links)
- Deformation of log-likelihood loss function for multiclass boosting (Q1784701) (← links)
- Process consistency for AdaBoost. (Q1884601) (← links)
- Boosting \(k\)-NN for categorization of natural scenes (Q1943405) (← links)
- Random classification noise defeats all convex potential boosters (Q1959553) (← links)
- Calibrating AdaBoost for phoneme classification (Q2001122) (← links)
- SVM-boosting based on Markov resampling: theory and algorithm (Q2057733) (← links)
- A new accelerated proximal boosting machine with convergence rate \(O(1/t^2)\) (Q2103099) (← links)
- Utilizing adaptive boosting to detect quantum steerability (Q2142590) (← links)
- A precise high-dimensional asymptotic theory for boosting and minimum-\(\ell_1\)-norm interpolated classifiers (Q2148995) (← links)
- Accelerated gradient boosting (Q2425242) (← links)
- A boosting method with asymmetric mislabeling probabilities which depend on covariates (Q2512782) (← links)
- Consistency and convergence rate for nearest subspace classifier (Q4603717) (← links)
- Boosting in the Presence of Outliers: Adaptive Classification With Nonconvex Loss Functions (Q4962433) (← links)
- Toward Efficient Ensemble Learning with Structure Constraints: Convergent Algorithms and Applications (Q5060788) (← links)
- Optimization by Gradient Boosting (Q5870986) (← links)
- Fully corrective gradient boosting with squared hinge: fast learning rates and early stopping (Q6072435) (← links)
- Boosting simple learners (Q6566593) (← links)
- Fast iterative regularization by reusing data (Q6583087) (← links)
- The vanishing learning rate asymptotic for linear \(L^2\)-boosting (Q6617090) (← links)
- A new integrated discrimination improvement index via odds (Q6640117) (← links)
