Selected Papers

Approximate Cross-Validation with Low-Rank Data in High Dimensions
W. Stephenson, M. Udell, and T. Broderick
Advances in Neural Information Processing Systems (NeurIPS), 2020
[arxiv][url][bib]

Scalable Semidefinite Programming
A. Yurtsever, J. Tropp, O. Fercoq, M. Udell, and V. Cevher
SIAM Journal on Mathematics of Data Science (SIMODS), 2020
[arxiv][bib]

Missing Value Imputation for Mixed Data Through Gaussian Copula
Y. Zhao and M. Udell
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[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]

An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity
L. Ding, A. Yurtsever, V. Cevher, J. Tropp, and M. Udell
Major Revision at SIOPT, 2020
Winner of 2017 INFORMS Optimization Society student paper prize
[arxiv][pdf][slides][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]

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage
A. Yurtsever, M. Udell, J. Tropp, and V. Cevher
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017
Oral Presentation
[arxiv][pdf][url][slides][bib][video]