Pages that link to "Item:Q1946480"

The following pages link to Concentration estimates for learning with unbounded sampling (Q1946480):

Displaying 36 items.

• Statistical consistency of coefficient-based conditional quantile regression (Q290691) (← links)
• Regularized least square regression with unbounded and dependent sampling (Q369717) (← links)
• Integral operator approach to learning theory with unbounded sampling (Q371679) (← links)
• Learning with coefficient-based regularization and \(\ell^1\)-penalty (Q380980) (← links)
• Quantile regression with \(\ell_1\)-regularization and Gaussian kernels (Q457695) (← links)
• Constructive analysis for coefficient regularization regression algorithms (Q491841) (← links)
• Concentration estimates for learning with \(\ell ^{1}\)-regularizer and data dependent hypothesis spaces (Q550498) (← links)
• Unified approach to coefficient-based regularized regression (Q651513) (← links)
• Statistical analysis of the moving least-squares method with unbounded sampling (Q726158) (← links)
• Relative deviation learning bounds and generalization with unbounded loss functions (Q1714946) (← links)
• Constructive analysis for least squares regression with generalized \(K\)-norm regularization (Q1724159) (← links)
• Coefficient-based \(l^q\)-regularized regression with indefinite kernels and unbounded sampling (Q1784975) (← links)
• System identification using kernel-based regularization: new insights on stability and consistency issues (Q1797024) (← links)
• On the convergence rate of kernel-based sequential greedy regression (Q1938256) (← links)
• ERM learning with unbounded sampling (Q1943018) (← links)
• Bayesian frequentist bounds for machine learning and system identification (Q2097759) (← links)
• Optimal convergence rates of high order Parzen windows with unbounded sampling (Q2251679) (← links)
• Learning with correntropy-induced losses for regression with mixture of symmetric stable noise (Q2300760) (← links)
• Optimal rates for coefficient-based regularized regression (Q2330932) (← links)
• Distributed learning with multi-penalty regularization (Q2415399) (← links)
• Quantitative bounds for concentration-of-measure inequalities and empirical regression: the independent case (Q2422732) (← links)
• Deterministic error bounds for kernel-based learning techniques under bounded noise (Q2665700) (← links)
• Unifying presampling via concentration bounds (Q2695631) (← links)
• Learning without concentration (Q2796408) (← links)
• Online regression with unbounded sampling (Q2885522) (← links)
• (Q3131335) (← links)
• Analysis of Regression Algorithms with Unbounded Sampling (Q3386411) (← links)
• (Q5159408) (← links)
• Regularized modal regression with data-dependent hypothesis spaces (Q5204652) (← links)
• Thresholded spectral algorithms for sparse approximations (Q5267950) (← links)
• Learning rates for regularized least squares ranking algorithm (Q5356934) (← links)
• Learning with Convex Loss and Indefinite Kernels (Q5378314) (← links)
• Support vector machines regression with unbounded sampling (Q5379431) (← links)
• Coefficient-based regularized distribution regression (Q6187678) (← links)
• Maximum correntropy criterion regression models with tending-to-zero scale parameters (Q6541933) (← links)
• Least squares regression under weak moment conditions (Q6664838) (← links)