19 citations · 19 across the 7 of their papers we have counts for
7 papers
High-Dimensional Sequential Change Detection
Robert Malinas, Dogyoon Song, Benjamin D. Robinson +1
We address the problem of detecting a change in the distribution of a high-dimensional multivariate normal time series. Assuming that the post-change parameters are unknown and est…
Spectrally Robust Covariance Shrinkage for Hotelling's in High Dimensions
Benjamin D. Robinson, Van Latimer
We investigate covariance shrinkage for Hotelling's in the regime where the data dimension and the sample size grow in a fixed ratio -- without assuming that the popu…
The Local Ledoit-Peche Law
Van Latimer, Benjamin D. Robinson
Ledoit and Peche proved convergence of certain functions of a random covariance matrix's resolvent; we refer to this as the Ledoit-Peche law. One important application of their res…
An Improvement on the Hotelling Test Using the Ledoit-Wolf Nonlinear Shrinkage Estimator
Benjamin D. Robinson, Robert Malinas, Van Latimer +2
Hotelling's test is a classical approach for discriminating the means of two multivariate normal samples that share a population covariance matrix. Hotelling's test is not id…
High-Dimensional Covariance Shrinkage for Signal Detection
Benjamin D. Robinson, Robert Malinas, Alfred O. Hero
In this paper, we consider the problem of determining the presence of a given signal in a high-dimensional observation with unknown covariance matrix by using an adaptive matched f…
Fisher-Rao distance on the covariance cone
Joseph Wells, Mary Cook, Karleigh Pine +1
The Fisher-Rao geodesic distance on the statistical manifold consisting of zero-mean p-dimensional multivariate Gaussians appears without proof in several places (such as Steven Sm…
Space-Time Adaptive Detection at Low Sample Support
Benjamin D. Robinson, Robert Malinas, Alfred O. Hero
An important problem in space-time adaptive detection is the estimation of the large p-by-p interference covariance matrix from training signals. When the number of training signal…