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Browsing by Subject "Bayesian learning"
Now showing items 1-5 of 5
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Constrained Discretion and Central Bank Transparency
(Economic Research Initiatives at Duke (ERID), 2015-02-01)We develop and estimate a general equilibrium model to quantitatively assess the effects and welfare implications of central bank transparency. Monetary policy can deviate from active inflation stabilization and agents conduct ... -
Designing Subscription Services with Imperfect Information and Dynamic Learning
(2021)This dissertation studies how a subscription service provider offers contracts to customers without full information on their preferences. The first essay studies a mechanism design problem for business interruption (BI) ... -
Dynamic Models of Human Capital Accumulation
(2015)This dissertation consists of three separate essays that use dynamic models to better understand the human capital accumulation process. First, I analyze the role of migration in human capital accumulation and how migration ... -
Hierarchical Bayesian Learning Approaches for Different Labeling Cases
(2015)The goal of a machine learning problem is to learn useful patterns from observations so that appropriate inference can be made from new observations as they become available. Based on whether labels are available for training ... -
Towards Better Representations with Deep/Bayesian Learning
(2018)Deep learning and Bayesian Learning are two popular research topics in machine learning. They provide the flexible representations in the complementary manner. Therefore, it is desirable to take the best from both fields. ...
