| 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 | 59 | 2015 |
| 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 | 59 | 2015 |
| 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 | 59 | 2015 |
| Asynchronous parallel algorithms for nonconvex big-data optimization. part ii: Complexity and numerical results L Cannelli, F Facchinei, V Kungurtsev, G Scutari arXiv preprint arXiv:1701.04900, 2017 | 47* | 2017 |
| A stabilized SQP method: global convergence PE Gill, V Kungurtsev, DP Robinson IMA Journal of Numerical Analysis 37 (1), 407-443, 2017 | 36 | 2017 |
| A stabilized SQP method: superlinear convergence PE Gill, V Kungurtsev, DP Robinson Mathematical Programming 163 (1-2), 369-410, 2017 | 26 | 2017 |
| Second-order guarantees of distributed gradient algorithms A Daneshmand, G Scutari, V Kungurtsev SIAM Journal on Optimization 30 (4), 3029-3068, 2020 | 24 | 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 | 17 | 2016 |
| 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 | 16 | 2017 |
| Sensitivity-based economic NMPC with a path-following approach E Suwartadi, V Kungurtsev, J Jäschke Processes 5 (1), 8, 2017 | 15 | 2017 |
| Second-derivative sequential quadratic programming methods for nonlinear optimization V Kungurtsev UC San Diego, 2013 | 14 | 2013 |
| Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity F Facchinei, V Kungurtsev, L Lampariello, G Scutari arXiv preprint arXiv:1709.03384, 2017 | 13 | 2017 |
| Sequential quadratic programming methods for parametric nonlinear optimization V Kungurtsev, M Diehl Computational Optimization and Applications 59 (3), 475-509, 2014 | 12 | 2014 |
| Second-order guarantees of gradient algorithms over networks A Daneshmand, G Scutari, V Kungurtsev 2018 56th Annual Allerton Conference on Communication, Control, and …, 2018 | 11 | 2018 |
| A regularized SQP method with convergence to second-order optimal points PE Gill, V Kungurtsev, DP Robinson UCSD Center for computational mathematics technical report CCoM-13-4, 2013 | 11 | 2013 |
| Capacity sensitivity in additive non-gaussian noise channels M Egan, SM Perlaza, V Kungurtsev 2017 IEEE International Symposium on Information Theory (ISIT), 416-420, 2017 | 10 | 2017 |
| SQP methods for parametric nonlinear optimization V Kungurtsev, M Diehl Optimization Online, 1-35, 2014 | 9 | 2014 |
| A subsampling line-search method with second-order results E Bergou, Y Diouane, V Kunc, V Kungurtsev, CW Royer arXiv preprint arXiv:1810.07211, 2018 | 8 | 2018 |
| Asynchronous parallel nonconvex large-scale optimization L Cannelli, F Facchinei, V Kungurtsev, G Scutari 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 6 | 2017 |
| Stochastic gradient Langevin dynamics on a distributed network V Kungurtsev arXiv preprint arXiv:2001.00665, 2020 | 5 | 2020 |
Gesualdo ScutariSchool of Industrial Engineering, Purdue UniversityVerifierad e-postadress på purdue.edu
