3 citations · 6 across the 4 of their papers we have counts for
4 papers
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…
Inference on the proportion of variance explained in principal component analysis
Ronan Perry, Snigdha Panigrahi, Jacob Bien +1
Principal component analysis (PCA) is a longstanding and well-studied approach for dimension reduction. It rests upon the assumption that the underlying signal in the data has low…