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Vyacheslav Kungurtsev
Vyacheslav Kungurtsev
Verified email at fel.cvut.cz
Title
Cited by
Cited by
Year
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
682015
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
682015
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
682015
Asynchronous parallel algorithms for nonconvex optimization
L Cannelli, F Facchinei, V Kungurtsev, G Scutari
Mathematical Programming 184 (1), 121-154, 2020
65*2020
A stabilized SQP method: global convergence
PE Gill, V Kungurtsev, DP Robinson
IMA Journal of Numerical Analysis 37 (1), 407-443, 2017
462017
Second-order guarantees of distributed gradient algorithms
A Daneshmand, G Scutari, V Kungurtsev
SIAM Journal on Optimization 30 (4), 3029-3068, 2020
362020
A stabilized SQP method: superlinear convergence
PE Gill, V Kungurtsev, DP Robinson
Mathematical Programming 163 (1), 369-410, 2017
332017
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
242017
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 (3), 927-944, 2020
222020
Sequential quadratic programming methods for parametric nonlinear optimization
V Kungurtsev, M Diehl
Computational Optimization and Applications 59 (3), 475-509, 2014
202014
Sensitivity-based economic NMPC with a path-following approach
E Suwartadi, V Kungurtsev, J Jäschke
Processes 5 (1), 8, 2017
192017
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
192016
A subsampling line-search method with second-order results
EH Bergou, Y Diouane, V Kunc, V Kungurtsev, CW Royer
INFORMS Journal on Optimization, 2022
152022
Second-derivative sequential quadratic programming methods for nonlinear optimization
V Kungurtsev
University of California, San Diego, 2013
152013
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
13*2020
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
132020
Second-order guarantees of gradient algorithms over networks
A Daneshmand, G Scutari, V Kungurtsev
2018 56th Annual Allerton Conference on Communication, Control, and …, 2018
132018
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
122013
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
112021
A stochastic levenberg-marquardt method using random models with application to data assimilation
E Bergou, Y Diouane, V Kungurtsev, CW Royer
arXiv preprint arXiv:1807.02176 3, 2018
11*2018
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Articles 1–20