The following pages link to (Q3174050):
Displaying 50 items.
- Bayesian frequentist bounds for machine learning and system identification (Q2097759) (← links)
- On regularization of generalized maximum entropy for linear models (Q2100166) (← links)
- Multivariate sparse Laplacian shrinkage for joint estimation of two graphical structures (Q2101407) (← links)
- Revisiting feature selection for linear models with FDR and power guarantees (Q2111958) (← links)
- Dynamic networks with multi-scale temporal structure (Q2121707) (← links)
- Sparse Laplacian shrinkage with the graphical Lasso estimator for regression problems (Q2125484) (← links)
- Approximation to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations (Q2128624) (← links)
- Sparse high-dimensional linear regression. Estimating squared error and a phase transition (Q2131259) (← links)
- Iterative algorithm for discrete structure recovery (Q2131266) (← links)
- Adaptive log-density estimation (Q2131904) (← links)
- On the strong oracle property of concave penalized estimators with infinite penalty derivative at the origin (Q2131914) (← links)
- De-biasing the Lasso with degrees-of-freedom adjustment (Q2136990) (← links)
- A generative approach to modeling data with quantitative and qualitative responses (Q2140852) (← links)
- Ridge regression revisited: debiasing, thresholding and bootstrap (Q2148980) (← links)
- High-dimensional regression with potential prior information on variable importance (Q2152561) (← links)
- Change points detection and parameter estimation for multivariate time series (Q2153567) (← links)
- Random weighting in LASSO regression (Q2154956) (← links)
- Nonparametric estimation of the random coefficients model: an elastic net approach (Q2155297) (← links)
- Bayesian factor-adjusted sparse regression (Q2155305) (← links)
- Single-index composite quantile regression for ultra-high-dimensional data (Q2161022) (← links)
- A unifying framework of high-dimensional sparse estimation with difference-of-convex (DC) regularizations (Q2163076) (← links)
- Large-scale multivariate sparse regression with applications to UK Biobank (Q2170442) (← links)
- Robust post-selection inference of high-dimensional mean regression with heavy-tailed asymmetric or heteroskedastic errors (Q2172011) (← links)
- Robust change point detection method via adaptive LAD-Lasso (Q2175643) (← links)
- Nonconcave penalized estimation in sparse vector autoregression model (Q2180066) (← links)
- Nonparametric variable selection and its application to additive models (Q2183769) (← links)
- Hierarchical inference for genome-wide association studies: a view on methodology with software (Q2184390) (← links)
- Debiasing the debiased Lasso with bootstrap (Q2192302) (← links)
- Robust machine learning by median-of-means: theory and practice (Q2196199) (← links)
- Lasso guarantees for \(\beta \)-mixing heavy-tailed time series (Q2196212) (← links)
- Statistical analysis of sparse approximate factor models (Q2199708) (← links)
- Fundamental limits of exact support recovery in high dimensions (Q2203616) (← links)
- Sparse directed acyclic graphs incorporating the covariates (Q2208417) (← links)
- Model selection for high-dimensional linear regression with dependent observations (Q2215720) (← links)
- Which bridge estimator is the best for variable selection? (Q2215760) (← links)
- Sparse identification of truncation errors (Q2222522) (← links)
- Sparse regression: scalable algorithms and empirical performance (Q2225311) (← 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)
- Rejoinder: ``Sparse regression: scalable algorithms and empirical performance'' (Q2225319) (← links)
- Consistent group selection with Bayesian high dimensional modeling (Q2226716) (← links)
- Parallel integrative learning for large-scale multi-response regression with incomplete outcomes (Q2242011) (← links)
- Bayesian model selection for high-dimensional Ising models, with applications to educational data (Q2242152) (← links)
- A significance test for the lasso (Q2249837) (← links)
- Discussion: ``A significance test for the lasso'' (Q2249838) (← links)
- Rejoinder: ``A significance test for the lasso'' (Q2249839) (← links)
- Lasso with long memory regression errors (Q2250693) (← links)
- High-dimensional mean estimation via \(\ell_1\) penalized normal likelihood (Q2252887) (← links)
- Sparse wavelet regression with multiple predictive curves (Q2254158) (← links)
- Sparse semiparametric discriminant analysis (Q2256757) (← links)
- High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
