4 papers
Generalized Data Thinning Using Sufficient Statistics
Ameer Dharamshi, Anna Neufeld, Keshav Motwani +3
Our goal is to develop a general strategy to decompose a random variable into multiple independent random variables, without sacrificing any information about unknown parameter…
Thinning a Wishart Random Matrix
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In th…
Decomposing Gaussians with Unknown Covariance
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Common workflows in machine learning and statistics rely on the ability to partition the information in a data set into independent portions. Recent work has shown that this may be…
Discussion of "Data fission: splitting a single data point"
Anna Neufeld, Ameer Dharamshi, Lucy L. Gao +2
Leiner et al. [2023] introduce an important generalization of sample splitting, which they call data fission. They consider two cases of data fission: P1 fission and P2 fission. Wh…