Pages that link to "Item:Q2880932"
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The following pages link to Classification with Gaussians and convex loss (Q2880932):
Displaying 28 items.
- An oracle inequality for regularized risk minimizers with strongly mixing observations (Q373424) (← links)
- Quantile regression with \(\ell_1\)-regularization and Gaussian kernels (Q457695) (← links)
- Logistic classification with varying gaussians (Q534984) (← links)
- Learning from non-identical sampling for classification (Q541601) (← links)
- Classification with Gaussians and convex loss. II: Improving error bounds by noise conditions (Q547325) (← links)
- Covering numbers of Gaussian reproducing kernel Hilbert spaces (Q555034) (← links)
- A new comparison theorem on conditional quantiles (Q656698) (← links)
- Multi-kernel regularized classifiers (Q870343) (← links)
- Calibration of \(\epsilon\)-insensitive loss in support vector machines regression (Q1730072) (← links)
- Optimal regression rates for SVMs using Gaussian kernels (Q1951100) (← links)
- Conditional quantiles with varying Gaussians (Q1955538) (← links)
- Unregularized online algorithms with varying Gaussians (Q2035494) (← links)
- Distributed regularized least squares with flexible Gaussian kernels (Q2036424) (← links)
- Learning rates of kernel-based robust classification (Q2157879) (← links)
- Learning with sample dependent hypothesis spaces (Q2389476) (← links)
- Employing different loss functions for the classification of images via supervised learning (Q2440581) (← links)
- Learning rates for the risk of kernel-based quantile regression estimators in additive models (Q2805231) (← links)
- Learning rates of regression with \(q\)-norm loss and threshold (Q2835987) (← links)
- Analysis to Neyman-Pearson classification with convex loss function (Q3538596) (← links)
- Comparison theorems on large-margin learning (Q5022946) (← links)
- A STUDY ON THE ERROR OF DISTRIBUTED ALGORITHMS FOR BIG DATA CLASSIFICATION WITH SVM (Q5370777) (← links)
- Learning with Convex Loss and Indefinite Kernels (Q5378314) (← links)
- A Note on Support Vector Machines with Polynomial Kernels (Q5380381) (← links)
- Learning Rates for Classification with Gaussian Kernels (Q5380881) (← links)
- Online Classification with Varying Gaussians (Q5851123) (← links)
- Optimal learning with Gaussians and correntropy loss (Q5856264) (← links)
- Large margin unified machines with non-i.i.d. process (Q6599669) (← links)
- Convergence analysis for complementary-label learning with kernel ridge regression (Q6636868) (← links)
