activity
20162024
most citedDynamic matrix recovery from incomplete observations under an exact low-rank constraint

14 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2024

Robust Broadband Beamforming using Bilinear Programming

Nakul Singh, Coleman DeLude, Mark A. Davenport +1

We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers sta…

stat.ML2023

Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning

Austin Xu, Andrew D. McRae, Jingyan Wang +2

We introduce a new type of query mechanism for collecting human feedback, called the perceptual adjustment query ( PAQ). Being both informative and cognitively lightweight, the PAQ…

eess.SP2023

Distance preservation in state-space methods for detecting causal interactions in dynamical systems

Matthew O'Shaughnessy, Mark Davenport, Christopher Rozell

We analyze the popular ``state-space'' class of algorithms for detecting casual interaction in coupled dynamical systems. These algorithms are often justified by Takens' embedding…

eess.SP20231 cited

Learned Proximal Operator for Solving Seismic Deconvolution Problem

Peimeng Guan, Naveed Iqbal, Mark A. Davenport +1

Seismic deconvolution is an essential step in seismic data processing that aims to extract layer information from noisy observed traces. In general, this is an ill-posed problem wi…

stat.ML201614 cited

Dynamic matrix recovery from incomplete observations under an exact low-rank constraint

Liangbei Xu, Mark A. Davenport

Low-rank matrix factorizations arise in a wide variety of applications -- including recommendation systems, topic models, and source separation, to name just a few. In these and ma…