6 papers
Effects of Structural Allocation of Geometric Task Diversity in Linear Meta-Learning Models
Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova +2
Meta-learning aims to leverage information across related tasks to improve prediction on unlabeled data for new tasks when only a small number of labeled observations are available…
On Bayes factor functions
Saptati Datta, Riana Guha, Rachael Shudde +1
We describe Bayes factors functions based on the sampling distributions of \emph{z}, \emph{t}, , and \emph{F} statistics, using a class of inverse-moment prior distributions t…
Bayes factor functions for testing partial correlation coefficients
Saptati Datta
Partial correlation coefficients are widely applied in the social sciences to evaluate the relationship between two variables after accounting for the influence of others. In this…
Learning with Sparsely Permuted Data: A Robust Bayesian Approach
Abhisek Chakraborty, Saptati Datta
Data dispersed across multiple files are commonly integrated through probabilistic linkage methods, where even minimal error rates in record matching can significantly contaminate…
Differentially private Bayesian tests
Abhisek Chakraborty, Saptati Datta
Differential privacy has emerged as an significant cornerstone in the realm of scientific hypothesis testing utilizing confidential data. In reporting scientific discoveries, Bayes…
Bayes Factors Based on Test Statistics and Non-Local Moment Prior Densities
Saptati Datta, Rachael Shudde, Valen E. Johnson
We describe Bayes factors based on z, t, , and F statistics when non-local moment prior distributions are used to define alternative hypotheses. The non-local alternative prio…