Asynchronous parallel algorithms for nonconvex optimization L Cannelli, F Facchinei, V Kungurtsev, G Scutari Mathematical Programming 184 (1), 121-154, 2020 | 84* | 2020 |
Hybrid random/deterministic parallel algorithms for convex and nonconvex big data optimization A Daneshmand, F Facchinei, V Kungurtsev, G Scutari IEEE Transactions on Signal Processing 63 (15), 3914-3929, 2015 | 78 | 2015 |
Convergence and complexity analysis of a Levenberg–Marquardt algorithm for inverse problems EH Bergou, Y Diouane, V Kungurtsev Journal of Optimization Theory and Applications 185, 927-944, 2020 | 69 | 2020 |
Second-order guarantees of distributed gradient algorithms A Daneshmand, G Scutari, V Kungurtsev SIAM Journal on Optimization 30 (4), 3029-3068, 2020 | 66 | 2020 |
A stabilized SQP method: global convergence PE Gill, V Kungurtsev, DP Robinson IMA Journal of Numerical Analysis 37 (1), 407-443, 2017 | 54 | 2017 |
A stabilized SQP method: superlinear convergence PE Gill, V Kungurtsev, DP Robinson Mathematical Programming 163 (1), 369-410, 2017 | 40 | 2017 |
Efficient distribution similarity identification in clustered federated learning via principal angles between client data subspaces S Vahidian, M Morafah, W Wang, V Kungurtsev, C Chen, M Shah, B Lin Proceedings of the AAAI conference on artificial intelligence 37 (8), 10043 …, 2023 | 39 | 2023 |
A predictor-corrector path-following algorithm for dual-degenerate parametric optimization problems V Kungurtsev, J Jaschke SIAM Journal on Optimization 27 (1), 538-564, 2017 | 30 | 2017 |
A subsampling line-search method with second-order results EH Bergou, Y Diouane, V Kunc, V Kungurtsev, CW Royer INFORMS Journal on Optimization 4 (4), 403-425, 2022 | 29 | 2022 |
Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity F Facchinei, V Kungurtsev, L Lampariello, G Scutari Mathematics of Operations Research 46 (2), 595-627, 2021 | 29 | 2021 |
Sequential quadratic programming methods for parametric nonlinear optimization V Kungurtsev, M Diehl Computational Optimization and Applications 59, 475-509, 2014 | 28 | 2014 |
A shifted primal-dual penalty-barrier method for nonlinear optimization PE Gill, V Kungurtsev, DP Robinson SIAM Journal on Optimization 30 (2), 1067-1093, 2020 | 23 | 2020 |
A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results EH Bergou, Y Diouane, V Kungurtsev, CW Royer SIAM/ASA Journal on Uncertainty Quantification 10 (1), 507-536, 2022 | 22* | 2022 |
Elastic consistency: A general consistency model for distributed stochastic gradient descent G Nadiradze, I Markov, B Chatterjee, V Kungurtsev, D Alistarh arXiv preprint arXiv:2001.05918, 2020 | 22* | 2020 |
Sensitivity-based economic NMPC with a path-following approach E Suwartadi, V Kungurtsev, J Jäschke Processes 5 (1), 8, 2017 | 22 | 2017 |
On the effect of perturbations in first-order optimization methods with inertia and Hessian driven damping H Attouch, J Fadili, V Kungurtsev arXiv preprint arXiv:2106.16159, 2021 | 21 | 2021 |
Asynchronous optimization over graphs: Linear convergence under error bound conditions L Cannelli, F Facchinei, G Scutari, V Kungurtsev IEEE Transactions on Automatic Control 66 (10), 4604-4619, 2020 | 21 | 2020 |
Asynchronous parallel algorithms for nonconvex big-data optimization-part i: Model and convergence L Cannelli, F Facchinei, V Kungurtsev, G Scutari arXiv preprint arXiv:1607.04818, 2016 | 21 | 2016 |
Second-order guarantees of gradient algorithms over networks A Daneshmand, G Scutari, V Kungurtsev 2018 56th Annual Allerton Conference on Communication, Control, and …, 2018 | 16 | 2018 |
Second-derivative sequential quadratic programming methods for nonlinear optimization V Kungurtsev University of California, San Diego, 2013 | 16 | 2013 |