Pages that link to "Item:Q2920259"
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The following pages link to Covariance-regularized regression and classification for high dimensional problems (Q2920259):
Displaying 50 items.
- scout (Q23996) (← links)
- Missing values: sparse inverse covariance estimation and an extension to sparse regression (Q80804) (← links)
- Estimating sufficient reductions of the predictors in abundant high-dimensional regressions (Q116954) (← links)
- A method for generating realistic correlation matrices (Q386759) (← links)
- Prediction in abundant high-dimensional linear regression (Q391850) (← links)
- Covariance estimation: the GLM and regularization perspectives (Q449843) (← links)
- On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator (Q485922) (← links)
- Improved shrinkage estimator of large-dimensional covariance matrix under the complex Gaussian distribution (Q782294) (← links)
- An adapted linear discriminant analysis with variable selection for the classification in high-dimension, and an application to medical data (Q830539) (← links)
- Regularization in statistics (Q882931) (← links)
- Regularization through variable selection and conditional MLE with application to classification in high dimensions (Q958795) (← links)
- Feature selection in omics prediction problems using cat scores and false nondiscovery rate control (Q977653) (← links)
- Transposable regularized covariance models with an application to missing data imputation (Q993250) (← links)
- Ridge estimation of inverse covariance matrices from high-dimensional data (Q1659004) (← links)
- A SAEM algorithm for fused Lasso penalized nonlinear mixed effect models: application to group comparison in pharmacokinetics (Q1659496) (← links)
- Sparse causality network retrieval from short time series (Q1687426) (← links)
- AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow (Q2071349) (← links)
- Varying coefficient linear discriminant analysis for dynamic data (Q2084480) (← links)
- Fitting Laplacian regularized stratified Gaussian models (Q2147926) (← links)
- Joint estimation of heterogeneous exponential Markov random fields through an approximate likelihood inference (Q2189113) (← links)
- A procedure of linear discrimination analysis with detected sparsity structure for high-dimensional multi-class classification (Q2196123) (← links)
- Capturing between-tasks covariance and similarities using multivariate linear mixed models (Q2209832) (← links)
- Computationally efficient banding of large covariance matrices for ordered data and connections to banding the inverse Cholesky factor (Q2252883) (← links)
- Penalized regression combining the \( L_{1}\) norm and a correlation based penalty (Q2253826) (← links)
- Greedy Gaussian segmentation of multivariate time series (Q2324258) (← links)
- Sparse regularized discriminant analysis with application to microarrays (Q2359339) (← links)
- Bayesian shrinkage methods for partially observed data with many predictors (Q2441860) (← links)
- Random matrix theory in statistics: a review (Q2453609) (← links)
- \( \mathcal{G} \)-LIME: statistical learning for local interpretations of deep neural networks using global priors (Q2680795) (← links)
- A multilevel framework for sparse optimization with application to inverse covariance estimation and logistic regression (Q2830631) (← links)
- A covariance regression model (Q2883907) (← links)
- Penalized Classification using Fisher’s Linear Discriminant (Q3107201) (← links)
- Covariance structure approximation via gLasso in high-dimensional supervised classification (Q3168288) (← links)
- A Perturbation Method for Inference on Regularized Regression Estimates (Q3225803) (← links)
- A component lasso (Q3463403) (← links)
- Hard thresholding regression (Q4629285) (← links)
- A comparison of regularization methods applied to the linear discriminant function with high-dimensional microarray data (Q4922655) (← links)
- Variable Selection in Nonparametric Classification Via Measurement Error Model Selection Likelihoods (Q4975400) (← links)
- Variable selection of linear programming discriminant estimator (Q4976213) (← links)
- (Q4998957) (← links)
- (Q4998960) (← links)
- Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs (Q5027037) (← links)
- Bayesian Estimation of Gaussian Conditional Random Fields (Q5037819) (← links)
- The Dantzig Discriminant Analysis with High Dimensional Data (Q5177600) (← links)
- Replica analysis of overfitting in regression models for time-to-event data (Q5369371) (← links)
- Some equivalence relationships of regularized regressions (Q5376067) (← links)
- Partitioning predictors in multivariate regression models (Q5962738) (← links)
- Variable selection for high‐dimensional generalized linear model with block‐missing data (Q6049794) (← links)
- High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference (Q6093503) (← links)
- Co-clustering of spatially resolved transcriptomic data (Q6161883) (← links)
