Alp Yurtsever
Alp Yurtsever
Vahvistettu sähköpostiosoite verkkotunnuksessa umu.se - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
1142017
Sketchy decisions: Convex low-rank matrix optimization with optimal storage
A Yurtsever, M Udell, JA Tropp, V Cevher
International Conference on Artificial Intelligence and Statistics, 2017
842017
A universal primal-dual convex optimization framework
A Yurtsever, Q Tran-Dinh, V Cevher
arXiv preprint arXiv:1502.03123, 2015
562015
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
45*2019
Online adaptive methods, universality and acceleration
KY Levy, A Yurtsever, V Cevher
arXiv preprint arXiv:1809.02864, 2018
432018
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
362021
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
352017
Stochastic three-composite convex minimization
A Yurtsever, BC Vu, V Cevher
arXiv preprint arXiv:1701.09033, 2017
282017
Conditional gradient methods via stochastic path-integrated differential estimator
A Yurtsever, S Sra, V Cevher
International Conference on Machine Learning, 7282-7291, 2019
242019
Randomized single-view algorithms for low-rank matrix approximation
JA Tropp, A Yurtsever, M Udell, V Cevher
California Institute of Technology, 2017
24*2017
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
A Yurtsever, O Fercoq, F Locatello, V Cevher
International Conference on Machine Learning, 2018
232018
Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable Poisson phase retrieval
G Odor, YH Li, A Yurtsever, YP Hsieh, Q Tran-Dinh, ME Halabi, V Cevher
IEEE International Conference on Acoustics, Speech and Signal Processing, 2016
232016
An optimal-storage approach to semidefinite programming using approximate complementarity
L Ding, A Yurtsever, V Cevher, JA Tropp, M Udell
arXiv preprint arXiv:1902.03373, 2019
192019
Stochastic forward Douglas-Rachford splitting method for monotone inclusions
V Cevher, BC Vũ, A Yurtsever
Large-Scale and Distributed Optimization, 149-179, 2018
172018
Stochastic Frank-Wolfe for composite convex minimization
F Locatello, A Yurtsever, O Fercoq, V Cevher
arXiv preprint arXiv:1901.10348, 2019
16*2019
A conditional-gradient-based augmented Lagrangian framework
A Yurtsever, O Fercoq, V Cevher
International Conference on Machine Learning, 7272-7281, 2019
142019
Scalable convex methods for phase retrieval
A Yurtsever, YP Hsieh, V Cevher
6th IEEE International Workshop on Computational Advances in Multi-Sensor …, 2015
112015
A non-Euclidean gradient descent framework for non-convex matrix factorization
YP Hsieh, YC Kao, RK Mahabadi, A Yurtsever, A Kyrillidis, V Cevher
IEEE Transactions on Signal Processing 66 (22), 5917-5926, 2018
92018
Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates
A Yurtsever, A Gu, S Sra
arXiv preprint arXiv:2110.03274, 2021
2021
Three Operator Splitting with a Nonconvex Loss Function
A Yurtsever, V Mangalick, S Sra
arXiv preprint arXiv:2103.04568, 2021
2021
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