Nonparametric empirical Bayes methods for large-scale inference under heteroscedasticity
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Shrinkage methods for big and complex data analysis
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Large scale inference with structural information
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Incorporating prior knowledge into regularized regression
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High dimensional estimation and inference with side information
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Non-parametric models for large capture-recapture experiments with applications to DNA sequencing
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Adapting statistical learning for high risk scenarios
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On optimal signal representation for statistical learning and pattern recognition
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Noise benefits in expectation-maximization algorithms
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Disease risk estimation from case-control studies with sampling
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Improved size and effort estimation models for software maintenance
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Large-scale multiple hypothesis testing and simultaneous inference: compound decision theory and data driven procedures
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Essays on treatment effect and policy learning
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M-estimation and non-parametric estimation of a random diffusion equation-based population model for the transdermal transport of ethanol: deconvolution and uncertainty quantification
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Mutual information estimation and its applications to machine learning
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Leveraging training information for efficient and robust deep learning
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Using multi-level Bayesian hierarchical model to detect related multiple SNPs within multiple genes to disease risk
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Human pose estimation from a single view point
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Physics-informed machine learning techniques for the estimation and uncertainty quantification of breath alcohol concentration from transdermal alcohol biosensor data
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Enhancing model performance of regularization methods by incorporating prior information
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The dynamics of reasonable doubt
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Bayesian analysis of stochastic volatility models with Levy jumps
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Population modeling and Bayesian estimation for the deconvolution of blood alcohol concentration from transdermal alcohol biosensor data
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Information geometry of annealing paths for inference and estimation
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Estimation of dynamic models
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