3 papers
stat.ML2025
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…
stat.ME2025
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…
math.ST2024
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…