Deprecated: $wgMWOAuthSharedUserIDs=false is deprecated, set $wgMWOAuthSharedUserIDs=true, $wgMWOAuthSharedUserSource='local' instead [Called from MediaWiki\HookContainer\HookContainer::run in /var/www/html/w/includes/HookContainer/HookContainer.php at line 135] in /var/www/html/w/includes/Debug/MWDebug.php on line 372
Consistency and robustness of kernel-based regression in convex risk minimization - MaRDI portal

Consistency and robustness of kernel-based regression in convex risk minimization

From MaRDI portal
Publication:2469652

DOI10.3150/07-BEJ5102zbMath1129.62031arXiv0709.0626WikidataQ59196404 ScholiaQ59196404MaRDI QIDQ2469652

Ingo Steinwart, Andreas Christmann

Publication date: 6 February 2008

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0709.0626




Related Items

Error analysis on Hérmite learning with gradient dataRobust nonparametric kernel regression estimatorOn the robustness of regularized pairwise learning methods based on kernelsPrediction of dynamical time series using kernel based regression and smooth splinesLoan pricing under estimation riskFrameworks and results in distributionally robust optimizationFast rates of minimum error entropy with heavy-tailed noiseModification of the adaptive Nadaraya-Watson kernel method for nonparametric regression (simulation study)Learning rates for the kernel regularized regression with a differentiable strongly convex lossKernel-Based Partial Permutation Test for Detecting Heterogeneous Functional RelationshipUnnamed ItemDeep learning theory of distribution regression with CNNsEstimation of the bandwidth parameter in Nadaraya-Watson kernel non-parametric regression based on universal threshold levelFeasible generalized least squares using support vector regressionA review on consistency and robustness properties of support vector machines for heavy-tailed distributionsAdaptive kernel methods using the balancing principleThe performance of semi-supervised Laplacian regularized regression with the least square lossLearning with Convex Loss and Indefinite KernelsDetecting influential observations in kernel PCARobust pairwise learning with Huber lossRobust kernel-based distribution regressionLearning from dependent observationsOn qualitative robustness of support vector machinesIdentifying outliers using multiple kernel canonical correlation analysis with application to imaging geneticsOn a strategy to develop robust and simple tariffs from motor vehicle insurance dataA two-experiment approach to Wiener system identificationPerformance analysis of the LapRSSLG algorithm in learning theoryA statistical learning assessment of Huber regressionRobust learning from bites for data miningConsistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noiseAnalysis of support vector machines regressionAsymptotic normality of support vector machine variants and other regularized kernel methodsRobustness by reweighting for kernel estimators: an overviewPrivacy-Preserving Parametric Inference: A Case for Robust StatisticsTesting subspace restrictions in the presence of high dimensional nuisance parametersRobustness of reweighted least squares kernel based regressionError analysis of the kernel regularized regression based on refined convex losses and RKBSs



Cites Work