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From OLS to High-dimensional Linear Regression -
Linear regression is commonly used in statistical analysis, and is one of the most important tools we learn in an introductory statistics course. What happens when we extend the setting to high-dimensional data, that is, data with more variables than observations? This talk will look at issues that arise in regression with high-dimensional data, how frequentists and Bayesians solve the problem, and my research, a Bayesian-adjacent method that uses empirical priors for high-dimensional linear regression. 

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