7 citations · 8 across the 3 of their papers we have counts for
5 papers
Toeplitz Low-Rank Approximation with Sublinear Query Complexity
Michael Kapralov, Hannah Lawrence, Mikhail Makarov +2
We present a sublinear query algorithm for outputting a near-optimal low-rank approximation to any positive semidefinite Toeplitz matrix . In particu…
GULP: a prediction-based metric between representations
Enric Boix-Adsera, Hannah Lawrence, George Stepaniants +1
Comparing the representations learned by different neural networks has recently emerged as a key tool to understand various architectures and ultimately optimize them. In this work…
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging
Hannah Lawrence, David A. Barmherzig, Henry Li +2
Phase retrieval is the inverse problem of recovering a signal from magnitude-only Fourier measurements, and underlies numerous imaging modalities, such as Coherent Diffraction Imag…
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers
Hannah Lawrence, Jerry Li, Cameron Musco +1
We study how to estimate a nearly low-rank Toeplitz covariance matrix from compressed measurements. Recent work of Qiao and Pal addresses this problem by combining sparse ruler…
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition
Lin Chen, Qian Yu, Hannah Lawrence +1
We study the problem of switching-constrained online convex optimization (OCO), where the player has a limited number of opportunities to change her action. While the discrete anal…