171 citations · 624 across the 37 of their papers we have counts for
5 papers · 1 filter
Testing for high-dimensional network parameters in auto-regressive models
Lili Zheng, Garvesh Raskutti
High-dimensional auto-regressive models provide a natural way to model influence between actors given multi-variate time series data for time intervals. While there has bee…
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.…
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…
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…
Non-parametric Sparse Additive Auto-regressive Network Models
Hao Henry Zhou, Garvesh Raskutti
Consider a multi-variate time series where which may represent spike train responses for multiple neurons in a brain, crime event data acro…