| 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 | 260 | 2017 |
| 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 | 173 | 2021 |
| 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 | 123 | 2017 |
| 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 | 120 | 2019 |
| Online adaptive methods, universality and acceleration KY Levy, A Yurtsever, V Cevher Advances in neural information processing systems 31, 2018 | 109 | 2018 |
| 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 | 95 | 2017 |
| A universal primal-dual convex optimization framework A Yurtsever, Q Tran-Dinh, V Cevher arXiv preprint arXiv:1502.03123, 2015 | 70 | 2015 |
| Conditional gradient methods via stochastic path-integrated differential estimator A Yurtsever, S Sra, V Cevher International Conference on Machine Learning, 7282-7291, 2019 | 60 | 2019 |
| 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 | 48 | 2018 |
| 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 | 44 | 2021 |
| A conditional-gradient-based augmented Lagrangian framework A Yurtsever, O Fercoq, V Cevher International Conference on Machine Learning, 7272-7281, 2019 | 42 | 2019 |
| Stochastic three-composite convex minimization A Yurtsever, BC Vu, V Cevher Advances in Neural Information Processing Systems 29, 2016 | 36 | 2016 |
| 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 | 35 | 2016 |
| Stochastic Frank-Wolfe for composite convex minimization F Locatello, A Yurtsever, O Fercoq, V Cevher Advances in Neural Information Processing Systems 32, 2019 | 33* | 2019 |
| Randomized single-view algorithms for low-rank matrix approximation JA Tropp, A Yurtsever, M Udell, V Cevher California Institute of Technology, 2017 | 33* | 2017 |
| Stochastic forward Douglas-Rachford splitting method for monotone inclusions V Cevher, BC Vũ, A Yurtsever Large-Scale and Distributed Optimization, 149-179, 2018 | 25 | 2018 |
| Scalable convex methods for phase retrieval A Yurtsever, YP Hsieh, V Cevher 6th IEEE International Workshop on Computational Advances in Multi-Sensor …, 2015 | 18 | 2015 |
| 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 | 16 | 2018 |
| 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 | 14 | 2022 |
| Three Operator Splitting with a Nonconvex Loss Function A Yurtsever, V Mangalick, S Sra International Conference on Machine Learning, 12267-12277, 2021 | 13 | 2021 |
Volkan CevherAssociate Professor, LIONS, EPFL. Amazon Scholar (AGI Foundations).Verificeret mail på epfl.ch