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Alp Yurtsever
Alp Yurtsever
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Titel
Zitiert von
Zitiert von
Jahr
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
2062017
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
1292021
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
1162017
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
1002019
Online adaptive methods, universality and acceleration
KY Levy, A Yurtsever, V Cevher
Advances in neural information processing systems 31, 2018
962018
Fixed-rank approximation of a positive-semidefinite matrix from streaming data
JA Tropp, A Yurtsever, M Udell, V Cevher
Advances in Neural Information Processing Systems 30, 2017
742017
A universal primal-dual convex optimization framework
A Yurtsever, Q Tran-Dinh, V Cevher
arXiv preprint arXiv:1502.03123, 2015
702015
Conditional gradient methods via stochastic path-integrated differential estimator
A Yurtsever, S Sra, V Cevher
International Conference on Machine Learning, 7282-7291, 2019
502019
An optimal-storage approach to semidefinite programming using approximate complementarity
L Ding, A Yurtsever, V Cevher, JA Tropp, M Udell
SIAM Journal on Optimization 31 (4), 2695-2725, 2021
402021
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
382018
Stochastic three-composite convex minimization
A Yurtsever, BC Vu, V Cevher
Advances in Neural Information Processing Systems 29, 2016
342016
A conditional-gradient-based augmented Lagrangian framework
A Yurtsever, O Fercoq, V Cevher
International Conference on Machine Learning, 7272-7281, 2019
332019
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
332016
Randomized single-view algorithms for low-rank matrix approximation
JA Tropp, A Yurtsever, M Udell, V Cevher
California Institute of Technology, 2017
29*2017
Stochastic Frank-Wolfe for composite convex minimization
F Locatello, A Yurtsever, O Fercoq, V Cevher
Advances in Neural Information Processing Systems 32, 2019
26*2019
Stochastic forward Douglas-Rachford splitting method for monotone inclusions
V Cevher, BC Vũ, A Yurtsever
Large-Scale and Distributed Optimization, 149-179, 2018
232018
Scalable convex methods for phase retrieval
A Yurtsever, YP Hsieh, V Cevher
6th IEEE International Workshop on Computational Advances in Multi-Sensor …, 2015
182015
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
132018
Three Operator Splitting with a Nonconvex Loss Function
A Yurtsever, V Mangalick, S Sra
International Conference on Machine Learning, 12267-12277, 2021
92021
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
A Yurtsever, T Birdal, V Golyanik
European Conference on Computer Vision, 352-369, 2022
82022
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