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Bayesian Methods for Skewed Response Including Longitudinal and Heteroscedastic Data
Effect of Risk Factors on Coronary Heart Disease
Fused Lasso and Tensor Covariance Learning with Robust Estimation
Non-Parametric and Semi-Parametric Estimation and Inference with Applications to Finance and Bioinformatics
On the Statistical Modeling of Count Data in High Dimensions
Parameter Sensitive Feature Selection for Learning on Large Datasets
Regression Methods for Skewed and Heteroscedastic Response with High-Dimensional Covariates
Scalable Nonconvex Optimization Algorithms
Semiparametric Survival Analysis Using Models with Log-Linear Median
Small Area Estimation with Random Effects Selection
Sparse Factor Auto-Regression for Forecasting Macroeconomic Time Series with Very Many Predictors
Sparse Feature and Element Selection in High-Dimensional Vector Autoregressive Models
Sparse Generalized PCA and Dependency Learning for Large-Scale Applications Beyond Gaussianity
Statistical Methods for Big Data and Their Applications in Biomedical Research
Studies of Joint Structure Sparsity Pursuit in the Applications of Hierarchical Variable Selection and Fused Lasso
Theories on Group Variable Selection in Multivariate Regression Models
Variable Selection of Correlated Predictors in Logistic Regression
Weighted Adaptive Methods for Multivariate Response Models with an HIV/Neurocognitive Application