289 citations · 1.2k across the 72 of their papers we have counts for
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Estimating Network Structure from Incomplete Event Data
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Multivariate Bernoulli autoregressive (BAR) processes model time series of events in which the likelihood of current events is determined by the times and locations of past events.…
Tensor Methods for Nonlinear Matrix Completion
Greg Ongie, Daniel Pimentel-Alarcón, Laura Balzano +2
In the low-rank matrix completion (LRMC) problem, the low-rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear alge…
Graph-based regularization for regression problems with alignment and highly-correlated designs
Yuan Li, Benjamin Mark, Garvesh Raskutti +3
Sparse models for high-dimensional linear regression and machine learning have received substantial attention over the past two decades. Model selection, or determining which featu…
Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes
Amin Jalali, Rebecca Willett
High-dimensional time series data exist in numerous areas such as finance, genomics, healthcare, and neuroscience. An unavoidable aspect of all such datasets is missing data, and d…
Network Estimation from Point Process Data
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Consider observing a collection of discrete events within a network that reflect how network nodes influence one another. Such data are common in spike trains recorded from biologi…