The following pages link to Empirical minimization (Q2494402):
Displaying 50 items.
- Inverse statistical learning (Q364201) (← links)
- General nonexact oracle inequalities for classes with a subexponential envelope (Q447832) (← links)
- Sharper lower bounds on the performance of the empirical risk minimization algorithm (Q637070) (← links)
- A high-dimensional Wilks phenomenon (Q718891) (← links)
- Regularization in kernel learning (Q847647) (← links)
- Empirical risk minimization for heavy-tailed losses (Q892246) (← links)
- Obtaining fast error rates in nonconvex situations (Q933417) (← links)
- Robust regression using biased objectives (Q1698865) (← links)
- Sharp oracle inequalities for least squares estimators in shape restricted regression (Q1750286) (← links)
- \(\ell _{1}\)-regularized linear regression: persistence and oracle inequalities (Q1930861) (← links)
- On the optimality of the empirical risk minimization procedure for the convex aggregation problem (Q1943331) (← links)
- Optimal upper and lower bounds for the true and empirical excess risks in heteroscedastic least-squares regression (Q1950830) (← links)
- Oracle inequalities for cross-validation type procedures (Q1950881) (← links)
- General oracle inequalities for model selection (Q1951973) (← links)
- On the optimality of the aggregate with exponential weights for low temperatures (Q1952438) (← links)
- A statistical learning assessment of Huber regression (Q2054280) (← links)
- Suboptimality of constrained least squares and improvements via non-linear predictors (Q2108490) (← links)
- Empirical variance minimization with applications in variance reduction and optimal control (Q2137023) (← links)
- Fast rates of minimum error entropy with heavy-tailed noise (Q2168008) (← links)
- Robust statistical learning with Lipschitz and convex loss functions (Q2174664) (← links)
- Convergence rates for empirical barycenters in metric spaces: curvature, convexity and extendable geodesics (Q2182123) (← links)
- Robust classification via MOM minimization (Q2203337) (← 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)
- Convergence rates of least squares regression estimators with heavy-tailed errors (Q2313287) (← links)
- Localized Gaussian width of \(M\)-convex hulls with applications to Lasso and convex aggregation (Q2325349) (← links)
- Minimax fast rates for discriminant analysis with errors in variables (Q2345118) (← links)
- Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder) (Q2373576) (← links)
- Empirical risk minimization: probabilistic complexity and stepsize strategy (Q2419551) (← links)
- Statistical performance of support vector machines (Q2426613) (← links)
- Ranking and empirical minimization of \(U\)-statistics (Q2426626) (← links)
- Empirical risk minimization is optimal for the convex aggregation problem (Q2435238) (← links)
- Local Rademacher complexities (Q2583411) (← links)
- Posterior concentration and fast convergence rates for generalized Bayesian learning (Q2666765) (← links)
- On the Optimality of Sample-Based Estimates of the Expectation of the Empirical Minimizer (Q3085585) (← links)
- Noisy discriminant analysis with boundary assumptions (Q3455256) (← links)
- FAST RATES FOR ESTIMATION ERROR AND ORACLE INEQUALITIES FOR MODEL SELECTION (Q3632389) (← links)
- (Q4558567) (← links)
- Confidence sets with expected sizes for Multiclass Classification (Q4637018) (← links)
- Learning Theory (Q4680882) (← links)
- (Q4969095) (← links)
- (Q4969103) (← links)
- Learning theory of minimum error entropy under weak moment conditions (Q5037873) (← links)
- (Q5053241) (← links)
- (Q5149262) (← links)
- (Q5159437) (← links)
- Classification with reject option (Q5295962) (← links)
- (Q5381137) (← links)
- Learning rates for partially linear support vector machine in high dimensions (Q5856267) (← links)
- Sample average approximation with heavier tails. I: Non-asymptotic bounds with weak assumptions and stochastic constraints (Q6038637) (← links)
