Papers

Papers below are listed by year of publication, or by year of submission before they are published.

For list of papers ordered by citation count, please see my google scholar profile.

Here are a few papers that give a good overview of my research.

Online Missing Value Imputation and Correlation Change Detection for Mixed-type Data via Gaussian Copula
Y. Zhao, E. Landgrebe, E. Shekhtman, and M. Udell
Submitted, 2020
[arxiv][bib]

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][bib]

Online Mixed Missing Value Imputation Using Gaussian Copula
E. Landgrebe, Y. Zhao, and M. Udell
ICML Workshop on the Art of Learning with Missing Values (Artemiss), 2020
[bib]

kFW: A Frank-Wolfe style algorithm with stronger subproblem oracles
L. Ding, J. Fan, and M. Udell
Submitted, 2020
[arxiv][bib]

Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
Y. Zhao and M. Udell
Advances in Neural Information Processing Systems (NeurIPS), 2020
[arxiv][bib]

Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time
I. Drori, A. Kharkar, W. R. Sickinger, B. Kates, Q. Ma, S. Ge, E. Dolev, B. Dietrich, D. P. Williamson, and M. Udell
IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), 2020
[arxiv][bib]

Efficient AutoML Pipeline Search with Matrix and Tensor Factorization
C. Yang, J. Fan, Z. Wu, and M. Udell
2020
[arxiv][bib]

Real-time AutoML
I. Drori, L. Liu, Q. Ma, J. Deykin, B. Kates, and M. Udell
Submitted, 2020
[bib]

Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering
J. Fan, C. Yang, and M. Udell
Major Revision at IEEE Trans. Signal Processing (TSP), 2020
[arxiv][bib]

An Information-Theoretic Approach to Persistent Environment Monitoring Through Low Rank Model Based Planning and Prediction
E. Ricci, M. Udell, and R. Knepper
2020
[arxiv][bib]

AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space
C. Yang, Z. Wu, J. Fan, and M. Udell
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[arxiv][url][bib]

On the regularity and conditioning of low rank semidefinite programs
L. Ding and M. Udell
Submitted to SIOPT, 2020
[arxiv][bib]

Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning
J. Fan, Y. Zhang, and M. Udell
Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
[arxiv][url][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]

Low-Rank Tucker Approximation of a Tensor From Streaming Data
Y. Sun, Y. Guo, C. Luo, J. Tropp, and M. Udell
Accepted at SIAM Journal on Mathematics of Data Science (SIMODS), 2020
[arxiv][pdf][slides][bib]

Scalable Semidefinite Programming
A. Yurtsever, J. Tropp, O. Fercoq, M. Udell, and V. Cevher
Submitted to SIAM Journal on Mathematics of Data Science (SIMODS), 2019
[arxiv][bib]

SysML: The New Frontier of Machine Learning Systems
A. Ratner, D. Alistarh, G. Alonso, D. G. Andersen, P. Bailis, S. Bird, N. Carlini, B. Catanzaro, E. Chung, B. Dally, J. Dean, I. S. Dhillon, A. G. Dimakis, P. Dubey, C. Elkan, G. Fursin, G. R. Ganger, L. Getoor, P. B. Gibbons, G. A. Gibson, J. E. Gonzalez, J. Gottschlich, S. Han, K. M. Hazelwood, F. Huang, M. Jaggi, K. G. Jamieson, M. I. Jordan, G. Joshi, R. Khalaf, J. Knight, J. Konecn\'y, T. Kraska, A. Kumar, A. Kyrillidis, J. Li, S. Madden, H. B. McMahan, E. Meijer, I. Mitliagkas, R. Monga, D. G. Murray, D. S. Papailiopoulos, G. Pekhimenko, T. Rekatsinas, A. Rostamizadeh, C. R\'e, C. D. Sa, H. Sedghi, S. Sen, V. Smith, A. Smola, D. Song, E. R. Sparks, I. Stoica, V. Sze, M. Udell, J. Vanschoren, S. Venkataraman, R. Vinayak, M. Weimer, A. G. Wilson, E. P. Xing, M. Zaharia, C. Zhang, and A. Talwalkar
CoRR, 2019
[arxiv][url][bib]

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery
J. Fan, L. Ding, Y. Chen, and M. Udell
Advances in Neural Information Processing Systems (NeurIPS), 2019
[arxiv][pdf][bib]

Randomized Sketching Algorithms for Low Memory Dynamic Optimization
R. Muthukumar, D. Kouri, and M. Udell
Under revision at SIOPT, 2019
[pdf][url][bib]

AutoML using Metadata Language Embeddings
I. Drori, L. Liu, S. Koorathota, N. Yi, J. Li, A. Moretti, J. Freire, and M. Udell
NeurIPS Workshop on Meta-Learning, 2019
[arxiv][pdf][bib]

OBOE: Collaborative Filtering for AutoML Model Selection
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]

``Why should you trust my explanation?'' Understanding uncertainty in LIME explanations
Y. Zhang, K. Song, Y. Sun, S. Tan, and M. Udell
ICML Workshop AI for Social Good, 2019
[arxiv][bib]

Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation
J. Tropp, A. Yurtsever, M. Udell, and V. Cevher
SIAM Scientific Computing (SISC), 2019
[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, 2019
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
[pdf][url][slides][bib][video]

Online High-Rank Matrix Completion
J. Fan and M. Udell
Computer Vision and Pattern Recognition (CVPR), 2019
Oral Presentation
[pdf][bib]

Optimal Design of Efficient Rooftop Photovoltaic Arrays
M. Udell and O. Toole
INFORMS Journal on Applied Analytics (Interfaces), 2019
Second place in 2017 INFORMS Doing Good with Good OR Paper Competition
[pdf][url][bib]

Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved
J. Chen, N. Kallus, X. Mao, G. Svacha, and M. Udell
FAT*: Conference on Fairness, Accountability, and Transparency, 2019
[arxiv][pdf][slides][bib]

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

Dynamic Assortment Personalization in High Dimensions
N. Kallus and M. Udell
Operations Research, 2019
[arxiv][url][bib]

Tensor Random Projection for Low Memory Dimension Reduction
Y. Sun, Y. Guo, J. Tropp, and M. Udell
NeurIPS Workshop on Relational Representation Learning, 2018
[pdf][url][bib]

More Practical Sketching Algorithms for Low-Rank Matrix Approximation
J. Tropp, A. Yurtsever, M. Udell, and V. Cevher
California Institute of Technology ACM Technical Report 2018-01, 2018
[pdf][bib]

OBOE: Collaborative Filtering for AutoML Initialization (workshop version)
C. Yang, Y. Akimoto, D. Kim, and M. Udell
NeurIPS Workshop on Automated Machine Learning, 2018
[arxiv][pdf][url][bib]

Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
S. Zhou, S. Gupta, and M. Udell
Advances in Neural Information Processing Systems, 2018
Spotlight presentation
[arxiv][pdf][slides][bib][video]

Causal Inference with Noisy and Missing Covariates via Matrix Factorization
N. Kallus, X. Mao, and M. Udell
Advances in Neural Information Processing Systems, 2018
[arxiv][code][bib]

Frank-Wolfe Style Algorithms for Large Scale Optimization
L. Ding and M. Udell
Large-Scale and Distributed Optimization, 2018
[arxiv][pdf][bib]

Matrix Factorization for Missing Value Imputation and Sparse Data Reconstruction
N. Sengupta, M. Udell, N. Srebro, and J. Evans
Submitted, 2017
[bib]

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
J. Tropp, A. Yurtsever, M. Udell, and V. Cevher
Advances in Neural Information Processing Systems, 2017
[arxiv][pdf][url][bib]

Graph-Regularized Generalized Low Rank Models
M. Paradkar and M. Udell
CVPR Workshop on Tensor Methods in Computer Vision, 2017
[pdf][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]

Disciplined Multi-Convex Programming
X. Shen, S. Diamond, M. Udell, Y. Gu, and S. Boyd
Chinese Control and Decision Conference (CCDC), 2017
Best Student Paper
[arxiv][bib]

Practical Sketching Algorithms for Low-Rank Matrix Approximation
J. Tropp, A. Yurtsever, M. Udell, and V. Cevher
SIAM Journal of Matrix Analysis and Applications (SIMAX), 2017
[arxiv][pdf][url][bib]

The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM
D. Davis, B. Edmunds, and M. Udell
Advances in Neural Information Processing Systems, 2016
[arxiv][pdf][bib]

Discovering Patient Phenotypes Using Generalized Low Rank Models
A. Schuler, V. Liu, J. Wan, A. Callahan, M. Udell, D. Stark, and N. Shah
Pacific Symposium on Biocomputing (PSB), 2016
[pdf][url][bib]

Revealed Preference at Scale: Learning Personalized Preferences from Assortment Choices
N. Kallus and M. Udell
The 2016 ACM Conference on Economics and Computation, 2016
[pdf][url][bib]

Learning Preferences from Assortment Choices in a Heterogeneous Population
N. Kallus and M. Udell
ICML Workshop on Computational Frameworks for Personalization, 2016
[arxiv][bib]

Generalized Low Rank Models
M. Udell, C. Horn, R. Zadeh, and S. Boyd
Foundations and Trends in Machine Learning, 2016
[arxiv][pdf][url][slides][code][bib]

Bounding Duality Gap for Separable Problems with Linear Constraints
M. Udell and S. Boyd
Computational Optimization and Applications, 2016
[arxiv][pdf][url][bib]

Generalized Low Rank Models
M. Udell
Stanford University Thesis, 2015
[pdf][code][bib]

Revenue Maximization for Broadband Service Providers Using Revenue Capacity
H. Mehmood, M. Udell, and J. Cioffi
IEEE Global Communications Conference, 2015
[pdf][bib]

PCA on a Data Frame
M. Udell and S. Boyd
2015
[pdf][code][bib]

Factorization for Analog-to-Digital Matrix Multiplication
E. Lee, M. Udell, and S. Wong
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015
[pdf][url][bib]

Beyond Principal Component Analysis (PCA)
M. Udell and S. Boyd
Biomedical Computation Review, 2014
[pdf][url][bib]

Convex Optimization in Julia
M. Udell, K. Mohan, D. Zeng, J. Hong, S. Diamond, and S. Boyd
SC14 Workshop on High Performance Technical Computing in Dynamic Languages, 2014
[arxiv][code][bib]

Generalized Low Rank Models
M. Udell, C. Horn, R. Zadeh, and S. Boyd
NeurIPS Workshop on Distributed Machine Learning and Matrix Computations, 2014
[pdf][code][bib]

Maximizing a Sum of Sigmoids
M. Udell and S. Boyd
2013
[pdf][code][bib]

Linear Bandits, Matrix Completion, and Recommendation Systems
M. Udell and R. Takapoui
NeurIPS Workshop on Large Scale Matrix Analysis and Inference, 2013
[pdf][bib]

Analyzing Patterns of Drug Use in Clinical Notes for Patient Safety
P. LePendu, Y. Liu, S. Iyer, M. Udell, and N. Shah
Proceedings of the AMIA Summits on Translational Science, 2012
[pdf][url][bib]