Pages that link to "Item:Q1043712"
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The following pages link to High-dimensional additive modeling (Q1043712):
Displaying 50 items.
- hgam (Q23148) (← links)
- Regularizing Double Machine Learning in Partially Linear Endogenous Models (Q115460) (← links)
- Kernel Knockoffs Selection for Nonparametric Additive Models (Q115586) (← links)
- Reluctant generalized additive modeling (Q141337) (← links)
- Flexible and Interpretable Models for Survival Data (Q144105) (← links)
- An introduction to recent advances in high/infinite dimensional statistics (Q268712) (← links)
- COBRA: a combined regression strategy (Q268720) (← links)
- Fast learning rate of multiple kernel learning: trade-off between sparsity and smoothness (Q366980) (← links)
- Polynomial spline estimation for generalized varying coefficient partially linear models with a diverging number of components (Q378915) (← links)
- Simultaneous confidence bands for sequential autoregressive fitting (Q392061) (← links)
- Correlated variables in regression: clustering and sparse estimation (Q394080) (← links)
- Consistency of support vector machines using additive kernels for additive models (Q433246) (← links)
- Semiparametric regression models with additive nonparametric components and high dimensional parametric components (Q435000) (← links)
- Transductive versions of the Lasso and the Dantzig selector (Q447611) (← links)
- Variable selection in infinite-dimensional problems (Q466987) (← links)
- CAM: causal additive models, high-dimensional order search and penalized regression (Q482906) (← links)
- High-dimensional Bayesian inference in nonparametric additive models (Q485930) (← links)
- Additive model selection (Q513754) (← links)
- On the \(L_p\) norms of kernel regression estimators for incomplete data with applications to classification (Q518885) (← links)
- Semi-varying coefficient models with a diverging number of components (Q548651) (← links)
- Sparsity in multiple kernel learning (Q620564) (← links)
- Generalization of constraints for high dimensional regression problems (Q645414) (← links)
- Oracle inequalities and optimal inference under group sparsity (Q651028) (← links)
- Learning non-parametric basis independent models from point queries via low-rank methods (Q741260) (← links)
- Statistical inference in sparse high-dimensional additive models (Q820814) (← links)
- Estimation and inference in generalized additive coefficient models for nonlinear interactions with high-dimensional covariates (Q888506) (← links)
- Functional additive regression (Q888512) (← links)
- On degeneracy and invariances of random fields paths with applications in Gaussian process modelling (Q899361) (← links)
- Variable selection in nonparametric additive models (Q988006) (← links)
- Interquantile shrinkage and variable selection in quantile regression (Q1615197) (← links)
- P-splines with an \(\ell_1\) penalty for repeated measures (Q1616325) (← links)
- Penalized likelihood and Bayesian function selection in regression models (Q1621251) (← links)
- Fast Bayesian model assessment for nonparametric additive regression (Q1621314) (← links)
- Monotone splines Lasso (Q1623607) (← links)
- Nonparametric independence screening via favored smoothing bandwidth (Q1643789) (← links)
- Fast learning rate of non-sparse multiple kernel learning and optimal regularization strategies (Q1657947) (← links)
- Regularized estimation for the least absolute relative error models with a diverging number of covariates (Q1659468) (← links)
- Variable selection for high dimensional Gaussian copula regression model: an adaptive hypothesis testing procedure (Q1662864) (← links)
- Sparse learning of the disease severity score for high-dimensional data (Q1693802) (← links)
- Regression with stagewise minimization on risk function (Q1727927) (← links)
- Improving the prediction performance of the Lasso by subtracting the additive structural noises (Q1729359) (← links)
- Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space (Q1750287) (← links)
- Fixed and random effects selection in nonparametric additive mixed models (Q1950841) (← links)
- A dimension reduction based approach for estimation and variable selection in partially linear single-index models with high-dimensional covariates (Q1950897) (← links)
- PAC-Bayesian estimation and prediction in sparse additive models (Q1951111) (← links)
- Dimension reduction and variable selection in case control studies via regularized likelihood optimization (Q1952024) (← links)
- A continuous analogue of the tensor-train decomposition (Q1987792) (← links)
- Empirical Bayes oracle uncertainty quantification for regression (Q1996760) (← links)
- Learning general sparse additive models from point queries in high dimensions (Q2007617) (← links)
- On histogram-based regression and classification with incomplete data (Q2044763) (← links)
