Andrew D. McRae

16 papers A* 2A 1Misc 1Journal 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms.
Math. Program.
Andrew D. McRae
2025 J jnl
Sensor network localization has a benign landscape after low-dimensional relaxation.
CoRR
Christopher Criscitiello, Andrew D. McRae, Quentin Rebjock, Nicolas Boumal
2024 J jnl
Benign Landscapes of Low-Dimensional Relaxations for Orthogonal Synchronization on General Graphs.
SIAM J. Optim.
Andrew D. McRae, Nicolas Boumal
2024 J jnl
New Equivalences between Interpolation and SVMs: Kernels and Structured Features.
SIAM J. Math. Data Sci.
Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar
2024 J jnl
Synchronization on circles and spheres with nonlinear interactions.
CoRR
Christopher Criscitiello, Quentin Rebjock, Andrew D. McRae, Nicolas Boumal
2023 J jnl
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features.
CoRR
Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar
2023 J jnl
Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer.
IEEE Trans. Inf. Theory
Andrew D. McRae, Justin Romberg, Mark A. Davenport
2023 A* conf
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning.
NeurIPS
Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
2023 J jnl
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning.
CoRR
Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
2022 Misc conf
Delta Distancing: A Lifting Approach to Localizing Items from User Comparisons.
ICASSP
Andrew D. McRae, Austin Xu, Jihui Jin, Namrata Nadagouda, Nauman Ahad, Peimeng Guan, Santhosh Karnik, Mark A. Davenport
2022 A conf
Harmless interpolation in regression and classification with structured features.
AISTATS
Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya K. Muthukumar
2022 — —
Structured Statistical Estimation via Optimization.
Andrew D. McRae
2021 J jnl
Harmless interpolation in regression and classification with structured features.
CoRR
Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya Muthukumar
2020 A* conf
Sample complexity and effective dimension for regression on manifolds.
NeurIPS
Andrew D. McRae, Justin Romberg, Mark A. Davenport
2020 J jnl
Sample complexity and effective dimension for regression on manifolds.
CoRR
Andrew D. McRae, Justin Romberg, Mark A. Davenport
2019 J jnl
Low-rank matrix completion and denoising under Poisson noise.
CoRR
Andrew D. McRae, Mark A. Davenport