Madeleine Udell
Madeleine Udell
Assistant Professor, Operations Research and Information Engineering, Cornell
Verifierad e-postadress på cornell.edu - Startsida
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Generalized low rank models
M Udell, C Horn, R Zadeh, S Boyd
Foundations and Trends in Machine Learning 9 (1), 2016
2872016
Convex optimization in Julia
M Udell, K Mohan, D Zeng, J Hong, S Diamond, S Boyd
2014 First Workshop for High Performance Technical Computing in Dynamic …, 2014
1162014
Practical sketching algorithms for low-rank matrix approximation
JA Tropp, A Yurtsever, M Udell, V Cevher
SIAM Journal on Matrix Analysis and Applications 38 (4), 1454-1485, 2017
962017
Why are big data matrices approximately low rank?
M Udell, A Townsend
SIAM Journal on Mathematics of Data Science 1 (1), 144-160, 2019
80*2019
Sketchy decisions: Convex low-rank matrix optimization with optimal storage
A Yurtsever, M Udell, J Tropp, V Cevher
Artificial intelligence and statistics, 1188-1196, 2017
782017
Fairness under unawareness: Assessing disparity when protected class is unobserved
J Chen, N Kallus, X Mao, G Svacha, M Udell
Proceedings of the conference on fairness, accountability, and transparency …, 2019
612019
Maximizing a sum of sigmoids
M Udell, S Boyd
532013
Bounding duality gap for separable problems with linear constraints
M Udell, S Boyd
Computational Optimization and Applications 64 (2), 355-378, 2016
50*2016
OBOE: Collaborative filtering for AutoML model selection
C Yang, Y Akimoto, DW Kim, M Udell
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
49*2019
Disciplined multi-convex programming
X Shen, S Diamond, M Udell, Y Gu, S Boyd
2017 29th Chinese Control And Decision Conference (CCDC), 895-900, 2017
362017
The sound of APALM clapping: Faster nonsmooth nonconvex optimization with stochastic asynchronous PALM
D Davis, B Edmunds, M Udell
Advances in Neural Information Processing Systems, 226-234, 2016
352016
Dynamic assortment personalization in high dimensions
N Kallus, M Udell
arXiv preprint arXiv:1610.05604, 2016
332016
Fixed-rank approximation of a positive-semidefinite matrix from streaming data
JA Tropp, A Yurtsever, M Udell, V Cevher
arXiv preprint arXiv:1706.05736, 2017
302017
Streaming low-rank matrix approximation with an application to scientific simulation
JA Tropp, A Yurtsever, M Udell, V Cevher
SIAM Journal on Scientific Computing 41 (4), A2430-A2463, 2019
282019
Causal inference with noisy and missing covariates via matrix factorization
N Kallus, X Mao, M Udell
arXiv preprint arXiv:1806.00811, 2018
252018
Discovering patient phenotypes using generalized low rank models
A Schuler, V Liu, J Wan, A Callahan, M Udell, DE Stark, NH Shah
Biocomputing 2016: Proceedings of the Pacific Symposium, 144-155, 2016
232016
Randomized single-view algorithms for low-rank matrix approximation
JA Tropp, A Yurtsever, M Udell, V Cevher
California Institute of Technology, 2017
212017
Incorporation of flexible objectives and time-linked simulation with flux balance analysis
EW Birch, M Udell, MW Covert
Journal of theoretical biology 345, 12-21, 2014
212014
Scalable semidefinite programming
A Yurtsever, JA Tropp, O Fercoq, M Udell, V Cevher
SIAM Journal on Mathematics of Data Science 3 (1), 171-200, 2021
192021
Low-rank tucker approximation of a tensor from streaming data
Y Sun, Y Guo, C Luo, J Tropp, M Udell
SIAM Journal on Mathematics of Data Science 2 (4), 1123-1150, 2020
182020
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Artiklar 1–20