Pages that link to "Item:Q1291160"

The following pages link to Risk bounds for model selection via penalization (Q1291160):

Displaying 50 items.

• Rates of convergence of posterior distributions. (Q1848879) (← links)
• Adaptive estimation in autoregression or \(\beta\)-mixing regression via model selection (Q1848887) (← links)
• Sharp adaptive estimation of linear functionals. (Q1848917) (← links)
• Random rates in anisotropic regression. (With discussion) (Q1848941) (← links)
• M-estimation using penalties or sieves (Q1866217) (← links)
• Free knot splines in concave extended linear modeling (Q1866234) (← links)
• Consistent covariate selection and post model selection inference in semiparametric regression. (Q1879925) (← links)
• Multiscale likelihood analysis and complexity penalized estimation. (Q1879941) (← links)
• Convergence rates for posterior distributions and adaptive estimation (Q1879965) (← links)
• Efficient robust nonparametric estimation in a semimartingale regression model (Q1930661) (← links)
• Adaptive estimation of linear functionals in functional linear models (Q1933354) (← links)
• Sharp oracle inequalities for aggregation of affine estimators (Q1940775) (← links)
• Adaptive estimation of the conditional intensity of marker-dependent counting processes (Q1944676) (← links)
• Honest adaptive confidence bands and self-similar functions (Q1950870) (← links)
• Oracle inequalities for cross-validation type procedures (Q1950881) (← links)
• Selecting the length of a principal curve within a Gaussian model (Q1951117) (← links)
• Optimal model selection in heteroscedastic regression using piecewise polynomial functions (Q1951154) (← links)
• Adaptive complexity regularization for linear inverse problems (Q1951768) (← links)
• Adaptive estimation of linear functionals by model selection (Q1951783) (← links)
• Simultaneous estimation of the mean and the variance in heteroscedastic Gaussian regression (Q1951804) (← links)
• Cumulative distribution function estimation under interval censoring case 1 (Q1951965) (← links)
• General oracle inequalities for model selection (Q1951973) (← links)
• Model selection by resampling penalization (Q1951992) (← links)
• Dimension reduction and variable selection in case control studies via regularized likelihood optimization (Q1952024) (← links)
• Plugin procedure in segmentation and application to hyperspectral image segmentation (Q1952077) (← links)
• The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (Q1952206) (← links)
• Inhomogeneous and anisotropic conditional density estimation from dependent data (Q1952241) (← links)
• Model selection and sharp asymptotic minimaxity (Q1955840) (← links)
• Adaptive kernel methods using the balancing principle (Q1959089) (← links)
• The Goldenshluger-Lepski method for constrained least-squares estimators over RKHSs (Q1983602) (← links)
• Nonparametric estimation of jump rates for a specific class of piecewise deterministic Markov processes (Q1983611) (← links)
• Approximate \(\ell_0\)-penalized estimation of piecewise-constant signals on graphs (Q1990576) (← links)
• Asymptotic analysis of model selection criteria for general hidden Markov models (Q1994901) (← links)
• Optimal estimation of variance in nonparametric regression with random design (Q1996785) (← links)
• Drift estimation on non compact support for diffusion models (Q2021393) (← links)
• Model selection for the robust efficient signal processing observed with small Lévy noise (Q2023459) (← links)
• Estimating a density, a hazard rate, and a transition intensity via the \(\rho\)-estimation method (Q2041794) (← links)
• Oracle posterior contraction rates under hierarchical priors (Q2044331) (← links)
• A MOM-based ensemble method for robustness, subsampling and hyperparameter tuning (Q2044333) (← links)
• Minimax bounds for Besov classes in density estimation (Q2044410) (← links)
• Estimates for the SVD of the truncated Fourier transform on \(L^2(\cosh (B|\cdot |))\) and stable analytic continuation (Q2048694) (← links)
• Set structured global empirical risk minimizers are rate optimal in general dimensions (Q2054522) (← links)
• Graph signal denoising using \(t\)-shrinkage priors (Q2123272) (← links)
• On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions (Q2136638) (← links)
• Empirical variance minimization with applications in variance reduction and optimal control (Q2137023) (← links)
• Adaptive density estimation on bounded domains under mixing conditions (Q2188474) (← links)
• On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising (Q2196192) (← links)
• Model selection: from theory to practice (Q2197389) (← links)
• A general framework for Bayes structured linear models (Q2215762) (← links)
• A look at robustness and stability of \(\ell_1\)-versus \(\ell_0\)-regularization: discussion of papers by Bertsimas et al. and Hastie et al. (Q2225318) (← links)