The following pages link to 10.1162/1532443041424337 (Q4823521):
Displaying 19 items.
- Tikhonov, Ivanov and Morozov regularization for support vector machine learning (Q285946) (← links)
- Sharp learning rates of coefficient-based \(l^q\)-regularized regression with indefinite kernels (Q370936) (← links)
- Oracle inequalities for support vector machines that are based on random entropy numbers (Q731974) (← links)
- Regularization in kernel learning (Q847647) (← links)
- On singular values of matrices with independent rows (Q882877) (← links)
- Using the doubling dimension to analyze the generalization of learning algorithms (Q923877) (← links)
- \(\ell _{1}\)-regularized linear regression: persistence and oracle inequalities (Q1930861) (← links)
- Penalized empirical risk minimization over Besov spaces (Q1952004) (← links)
- An elementary analysis of ridge regression with random design (Q2080945) (← links)
- ERM and RERM are optimal estimators for regression problems when malicious outliers corrupt the labels (Q2209821) (← links)
- Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions (Q2313281) (← links)
- Minimax fast rates for discriminant analysis with errors in variables (Q2345118) (← links)
- Statistical performance of support vector machines (Q2426613) (← links)
- Empirical minimization (Q2494402) (← links)
- Bandwidth selection in kernel empirical risk minimization via the gradient (Q2515491) (← links)
- (Q4558184) (← links)
- Variance-based regularization with convex objectives (Q5381122) (← links)
- Learning Bounds for Kernel Regression Using Effective Data Dimensionality (Q5706660) (← links)
- Adaptive metric dimensionality reduction (Q5964069) (← links)
