187 citations · 346 across the 26 of their papers we have counts for
31 papers
Stable estimation of pulses of unknown shape from multiple snapshots via ESPRIT
Meghna Kalra, Kiryung Lee
We consider the problem of resolving overlapping pulses from noisy multi-snapshot measurements, which has been a problem central to various applications including medical imaging a…
Max-affine regression via first-order methods
Seonho Kim, Kiryung Lee
We consider regression of a max-affine model that produces a piecewise linear model by combining affine models via the max function. The max-affine model ubiquitously arises in app…
Sketching low-rank matrices with a shared column space by convex programming
Rakshith S Srinivasa, Seonho Kim, Kiryung Lee
In many practical applications including remote sensing, multi-task learning, and multi-spectrum imaging, data are described as a set of matrices sharing a common column space. We…
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing
Kiryung Lee, Dominik Stöger
We consider the problem of reconstructing rank-one matrices from random linear measurements, a task that appears in a variety of problems in signal processing, statistics, and mach…
Approximately low-rank recovery from noisy and local measurements by convex program
Kiryung Lee, Rakshith Sharma Srinivasa, Marius Junge +1
Low-rank matrix models have been universally useful for numerous applications, from classical system identification to more modern matrix completion in signal processing and statis…
Max-Linear Regression by Convex Programming
Seonho Kim, Sohail Bahmani, Kiryung Lee
We consider the multivariate max-linear regression problem where the model parameters need to be estimated from inde…