Selected Papers

gcimpute: A Package for Missing Data Imputation
Y. Zhao and M. Udell
Accepted at Journal of Statistical Software, 2023
[arxiv][code][bib]

NysADMM: faster composite convex optimization via low-rank approximation
S. Zhao, Z. Frangella, and M. Udell
International Conference on Machine Learning (ICML), 2022
[arxiv][url][bib]

Randomized Nystr\"om Preconditioning
Z. Frangella, J. A. Tropp, and M. Udell
SIAM Journal on Matrix Analysis and Applications, 2022
[arxiv][url][bib]

An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity
L. Ding, A. Yurtsever, V. Cevher, J. Tropp, and M. Udell
SIAM Journal on Optimization (SIOPT), 2021
Winner of 2017 INFORMS Optimization Society student paper prize
[arxiv][pdf][slides][bib]

OBOE: Collaborative Filtering for AutoML Initialization
C. Yang, Y. Akimoto, D. Kim, and M. Udell
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
Oral presentation
[arxiv][pdf][url][bib]

Big Data is Low Rank
M. Udell
SIAG/OPT Views and News, 2019
[url][slides][bib]

Why are Big Data Matrices Approximately Low Rank?
M. Udell and A. Townsend
SIAM Mathematics of Data Science (SIMODS), 2019
[arxiv][bib]