Full publication list

This page reproduces the Google Scholar publication records supplied on 9 August 2026, in reverse chronological order. Google Scholar occasionally contains duplicate versions or incomplete metadata; those records are retained here rather than silently altered. For the live profile, see Google Scholar.

2026

• Restarting two-term nonlinear conjugate gradient methods based on a finite precision arithmetic analysis — M Kimiaei, S Babaie–Kafaki, V Kungurtsev, M Yousefi. Journal of Computational and Applied Mathematics 488, 117856

• Symplectic Neural Networks for learning Generalized Hamiltonians — H Choudhary, V Kungurtsev, C Gupta, M Leok, G Korpas. arXiv preprint arXiv:2606.27029

• Towards real time control of water engineering with nonlinear hyperbolic partial differential equations — F DiFonzo, M Holst, M Kimiaei, V Kungurtsev, S Qiu. Journal of Computational Science, 102945

• Structural Assessment for Understanding and Guiding Dataset Distillation in Discrete Token Space — Y Cao, J Gu, V Kungurtsev, Y Hu, J Hamari, Z Liu, M Zardadi. arXiv preprint arXiv:2606.21705

• Contemporary data-driven innovations in peptide-based therapeutic design — L Priyadarsinee, V Kungurtsev, V Kumar, B Chatterjee, GN Sastry, …. Briefings in Bioinformatics 27 (3), bbag220

• The stochastic Ravine accelerated gradient method with general extrapolation coefficients — H Attouch, J Fadili, V Kungurtsev. Journal of Optimization Theory and Applications 209 (1), 5

• Direct-search methods for decentralized blackbox optimization — E Bergou, Y Diouane, V Kungurtsev, CW Royer. Optimization Methods and Software, 1-22

• Antiproliferative activity, phytochemistry, network pharmacology, molecular docking and gene expression analysis of Maerua edulis extracts against human cervical … — IJL Lagu, R Letoluo, SW Kamau, JM Kuria, FM Musila, V Kungurtsev, …. BMC Complementary Medicine and Therapies 26 (1), 152

• Noncooperative Human-AI Agent Dynamics — D Waldner, V Kungurtsev, M Ashimosi. arXiv preprint arXiv:2603.16916

• Numerical Algorithms for Partially Segregated Elliptic Systems — F Bozorgnia, A Arakelyan, V Kungurtsev, J Valdman. arXiv preprint arXiv:2603.05991

• Concord: Concept-informed diffusion for dataset distillation — J Gu, H Wang, R Jia, S Vahidian, V Kungurtsev, W Jiang, Y Chen. 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV …

• Multistage Stochastic Programming for Rare Event Risk Mitigation in Power Systems Management — D Mastropietro, V Kungurtsev. arXiv preprint arXiv:2603.04734

• Towards Tsallis Fully Probabilistic Design — V Kungurtsev, G Russo. arXiv preprint arXiv:2602.23892

• Parallel variational quantum algorithms with gradient-informed restart to speed up optimization in the presence of barren plateaus — D Mastropietro, G Korpas, V Kungurtsev, J Marecek. IEEE Transactions on Quantum Engineering

• An efficient penalty decomposition algorithm for minimization over sparse symmetric sets — A Mousavi, M Kimiaei, S Babaie-Kafaki, V Kungurtsev. arXiv preprint arXiv:2601.12383

• A Three-Tier Time-Scale Architecture for Controlling Complex Nonlinear Systems — V Kungurtsev. arXiv preprint arXiv:2601.01621

• Probabilistic iterative hard thresholding for sparse learning — M Bergamaschi, A Cristofari, V Kungurtsev, F Rinaldi. Computational Optimization and Applications 93 (1), 57-83

2025

• Survey of Mathematical Models of and Numerical Methods for Fluid Dynamics Water Engineering — A Kumar, K Olimba, V Kungurtsev, FV Difonzo. arXiv preprint arXiv:2512.16351

• Fractional heat kernel for semi-supervised graph learning with small training sample size — F Bozorgnia, V Kungurtsev, S Kadyrov, M Yousefnezhad. arXiv preprint arXiv:2510.04440

• Machine learning algorithms for improving black box optimization solvers — M Kimiaei, V Kungurtsev. arXiv preprint arXiv:2509.25592

• Quasi-ergodic control of multi-periodic autoregressive processes: Formulation and examples — V Kungurtsev. arXiv preprint arXiv:2509.24729

• Leveraging Gradient Noise for Detection and Filtering of Byzantine Clients — L Errami, V Kungurtsev, EH Bergou. IEEE Access

• Machine Learning Algorithms for Improving Exact Classical Solvers in Mixed Integer Continuous Optimization — M Kimiaei, V Kungurtsev, B Olimba. arXiv preprint arXiv:2508.06906

• Optimal Control of Two-Phase Membrane Problem — F Bozorgnia, V Kungurtsev. Applied Mathematics & Optimization 92 (1), 8

• Binarizing physics-inspired gnns for combinatorial optimization — M Krutský, G Šír, V Kungurtsev, G Korpas. arXiv preprint arXiv:2507.13703

• A survey of multi agent reinforcement learning: Federated learning and cooperative and noncooperative decentralized regimes — K Cheruiyot, N Kiprotich, V Kungurtsev, K Mugo, V Mwirigi, M Ngesa. arXiv preprint arXiv:2507.06278

• Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations — V Kungurtsev, MC Naibei, A Anand, S Gros, H Tian, H Hamedmoghadam. arXiv preprint arXiv:2507.04356

• A stochastic-gradient-based interior-point algorithm for solving smooth bound-constrained optimization problems — FE Curtis, V Kungurtsev, DP Robinson, Q Wang. SIAM Journal on Optimization 35 (2), 1030-1059

• AI Alignment Foundations from First Principles: AI Ethics, Human and Social Considerations — V Kungurtsev. https://philpapers.org/archive/KUNAAF.pdf

• Optimisation techniques for variational quantum algorithms using noisy quantum processing hardware — G KORPAS, J Marecek, P INTALLURA, D MASTROPIETRO, …. US Patent App. 18/963,276

• Systems and methods for federated computer processing architecture and coordinated broadcast data messaging — G KORPAS, J KULCSAR, V KUNGURTSEV, W SHOOSMITH. US Patent App. 19/007,112

• Undecidable problems associated with variational quantum algorithms — G Korpas, V Kungurtsev, J Mareček. arXiv preprint arXiv:2503.23723

• Federated Sinkhorn — J Kulcsar, V Kungurtsev, G Korpas, G Giaconi, W Shoosmith. arXiv preprint arXiv:2502.07021

• Truss topology design under harmonic loads: peak power minimization with semidefinite programming: S. Ma et al. — S Ma, J Mareček, V Kungurtsev, M Tyburec. Structural and Multidisciplinary Optimization 68 (2), 40

• Parametric semidefinite programming: geometry of the trajectory of solutions — A Bellon, D Henrion, V Kungurtsev, J Mareček. Mathematics of Operations Research 50 (1), 410-430

• Planting 10 Million Trees with Lukenya University in Kenya: Methodology and Preliminary Observations and Forecasts — P Kyalo, V Kungurtsev, E Muli, S Pietsch, K Mugo, M Kaigongi, M Muasa, …. bioRxiv, 2025.01. 09.632148

• A class of diagonal quasi-Newton penalty decomposition algorithms for sparse bound-constrained nonconvex optimization — A Mousavi, M Kimiaei, S Babaie–Kafaki, V Kungurtsev

• Restarting nonlinear conjugate gradient methods — M Kimiaei, S Babaie–Kafaki, V Kungurtsev, M Yousefi

• Effect of Weather and Soil Management on Medicinal Compound Concentration in East African Arid Acacias: A Simulation Study — EW Kinyua, S Pietsch, E Muli, V Kungurtsev, S Neru, K Mugo. bioRxiv, 2025.01. 10.632480

• Cause” is Mechanistic Narrative within Scientific Domains: An Ordinary Language Philosophical Critique of” Causal Machine Learning — V Kungurtsev, LC Moore, M Krutsky. arXiv preprint arXiv:2501.05844

• The Stochastic Ravine Accelerated Gradient Method with General Extrapolation Coefficients — JM Fadili, H Attouch, V Kungurtsev. Journal of Optimization Theory and Applications

• A STOCHASTIC-GRADIENT-BASED INTERIOR-POINT ALGORITHM FOR SOLVING SMOOTH BOUND-CONSTRAINED — Curtis, Frank e., V Kungurtsev, Robinson, Daniel p., Q Wang. SIAM JOURNAL ON OPTIMIZATION 35 (2), 1030-1059

• AI Alignment Foundation from First Principles: Cybernetic, Mechatronic and Engineering Aspects — Kungurtsev, Vyacheslav, G Sir, M Krutsky. PhilArchive

• Group distributionally robust dataset distillation with risk minimization — S Vahidian, M Wang, J Gu, V Kungurtsev, W Jiang, Y Chen. Proceedings of the International Conference on Learning Representations (ICLR)

2024

• Towards diverse device heterogeneous federated learning via task arithmetic knowledge integration — M Morafah, V Kungurtsev, H Chang, C Chen, B Lin. Advances in Neural Information Processing Systems 37, 127834-127877

• Retraction-based direct search methods for derivative free riemannian optimization — V Kungurtsev, F Rinaldi, D Zeffiro. Journal of Optimization Theory and Applications 203 (2), 1710-1735

• Iteration complexity of variational quantum algorithms — V Kungurtsev, G Korpas, J Marecek, EY Zhu. Quantum 8, 1495

• Unlocking the potential of federated learning: The symphony of dataset distillation via deep generative latents — Y Jia, S Vahidian, J Sun, J Zhang, V Kungurtsev, NZ Gong, Y Chen. European Conference on Computer Vision, 18-33

• Learning generalized hamiltonians using fully symplectic mappings — H Choudhary, C Gupta, V Kungurtsev, M Leok, G Korpas. arXiv preprint arXiv:2409.11138

• Dataset distillation from first principles: Integrating core information extraction and purposeful learning — V Kungurtsev, Y Peng, J Gu, S Vahidian, A Quinn, F Idlahcen, Y Chen. arXiv preprint arXiv:2409.01410

• Federated sgd with local asynchrony — B Chatterjee, V Kungurtsev, D Alistarh. 2024 IEEE 44th International Conference on Distributed Computing Systems …

• Mini-batch stochastic subgradient for functional constrained optimization — NK Singh, I Necoara, V Kungurtsev. Optimization 73 (7), 2159-2185

• Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference — V Kungurtsev, A Khandelwal, PS Rastogi, B Chatterjee, J Mareček. arXiv preprint arXiv:2406.17831

• Learning dynamic Bayesian networks from data: Foundations, first principles and numerical comparisons — V Kungurtsev, F Idlahcen, P Rysavy, P Rytir, A Wodecki. arXiv preprint arXiv:2406.17585

• Efficient dataset distillation via minimax diffusion — J Gu, S Vahidian, V Kungurtsev, H Wang, W Jiang, Y You, Y Chen. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …

• Inexact direct-search methods for bilevel optimization problems — Y Diouane, V Kungurtsev, F Rinaldi, D Zeffiro. Computational Optimization and Applications 88 (2), 469-490

• Robust quantum gate complexity: foundations — J Aspman, V Kungurtsev, J Marecek. arXiv preprint arXiv:2404.15828

• Trilevel and multilevel optimization using monotone operator theory — A Shafiei, V Kungurtsev, J Marecek. Mathematical Methods of Operations Research 99 (1), 77-114

• Time-varying semidefinite programming: Path following a Burer–Monteiro factorization — A Bellon, M Dressler, V Kungurtsev, J Mareček, A Uschmajew. SIAM Journal on Optimization 34 (1), 1-26

• Spectral methods for quantum optimal control: Artificial boundary conditions — A Wodecki, J Marecek, V Kungurtsev, P Eichler, G Korpas, P Intallura. arXiv preprint arXiv:2403.14436

• The Effects of Transmission-Rights Pricing on Multi-Stage Electricity Markets — EB de Saint-Lienard, J Marecek, V Kungurtsev. arXiv preprint arXiv:2401.15772

• A direct-search method for decentralized derivative-free optimization — Y Diouane, EH Bergou, V Kungurtsev, CW Royer. Mathematical Optimization Society (MOS)

2023

• Scheduling a Multi-Product Pipeline: A Discretized MILP Formulation — A Wodecki, P Rytir, V Kungurtsev, J Marecek. arXiv preprint arXiv:2312.11381

• Pathfollowing for parametric mathematical programs with complementarity constraints — V Kungurtsev, J Jäschke. Optimization and Engineering 24 (4), 2795-2826

• When do curricula work in federated learning? — S Vahidian, S Kadaveru, W Baek, W Wang, V Kungurtsev, C Chen, …. 2023 IEEE/CVF International Conference on Computer Vision (ICCV), 5061-5071

• Decentralized bayesian learning with metropolis-adjusted hamiltonian monte carlo — V Kungurtsev, A Cobb, T Javidi, B Jalaian. Machine Learning 112 (8), 2791-2819

• Stochastic approximation for expectation objective and expectation inequality-constrained nonconvex optimization — F Facchinei, V Kungurtsev. arXiv preprint arXiv:2307.02943

• Quantum solutions to the privacy vs. utility tradeoff — S Chatterjee, V Kungurtsev. arXiv preprint arXiv:2307.03118

• 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 …

• Regularized quasi-monotone method for stochastic optimization: V. Kungurtsev, V. Shikhman — V Kungurtsev, V Shikhman. Optimization Letters 17 (5), 1215-1228

• On the ergodic control of ensembles in the presence of non-linear filters — V Kungurtsev, J Marecek, R Ghosh, R Shorten. Automatica 152, 110946

• Hybrid methods in polynomial optimisation — J Aspman, G Bareilles, V Kungurtsev, J Marecek, M Takáč. arXiv preprint arXiv:2305.16122

• A survey of quantum alternatives to randomized algorithms: Monte carlo integration and beyond — P Intallura, G Korpas, S Chakraborty, V Kungurtsev, R Lawrence, …. arXiv preprint arXiv:2303.04945

• A sequential quadratic programming method for optimization with stochastic objective functions, deterministic inequality constraints and robust subproblems — S Qiu, V Kungurtsev. arXiv preprint arXiv:2302.07947

• Decentralized asynchronous nonconvex stochastic optimization on directed graphs — V Kungurtsev, M Morafah, T Javidi, G Scutari. IEEE Transactions on Control of Network Systems 10 (4), 1796-1804

• Tame Riemannian stochastic approximation — J Aspman, V Kungurtsev, RR Seraji. arXiv preprint arXiv:2302.00709

• Riemannian stochastic approximation for minimizing tame nonsmooth objective functions — J Aspman, V Kungurtsev, RR Seraji. arXiv preprint arXiv:2302.00709

• Fleming-viot helps speed up variational quantum algorithms in the presence of barren plateaus — D Mastropietro, G Korpas, V Kungurtsev, J Marecek. arXiv preprint arXiv:2311.18090

2022

• A sensitivity assisted alternating directions method of multipliers for distributed optimization — D Krishnamoorthy, V Kungurtsev. 2022 IEEE 61st Conference on Decision and Control (CDC), 295-300

• A note on optimal tokamak control for fusion power simulation — M Holst, V Kungurtsev, S Mukherjee. arXiv preprint arXiv:2211.08984

• Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling — J Guidolin, V Kungurtsev, O Kuželka. arXiv preprint arXiv:2211.01774

• Distributed stochastic nonsmooth nonconvex optimization — V Kungurtsev. Operations Research Letters 50 (6), 627-631

• Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence — D Wu, V Kungurtsev, M Mondelli. arXiv preprint arXiv:2210.06819

• 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

• Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Reformulation — A Bellon, M Dressler, V Kungurtsev, J Marecek, A Uschmajew. arXiv preprint arXiv:2210.08387

• Diminishing stepsize methods for nonconvex composite problems via ghost penalties: from the general to the convex regular constrained case — F Facchinei, V Kungurtsev, L Lampariello, G Scutari. Optimization Methods and Software 37 (4), 1242-1268

• Stochastic langevin differential inclusions with applications to machine learning — FV Difonzo, V Kungurtsev, J Marecek. arXiv preprint arXiv:2206.11533

• Retraction based direct search methods for derivative free riemannian optimization — V Kungurtsev, F Rinaldi, D Zeffiro. arXiv preprint arXiv:2202.11052

• Simultaneous online model identification and production optimization using modifier adaptation — J Matias, V Kungurtsev, M Egan. Journal of Process Control 110, 110-120

• 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

• Mean-field analysis of piecewise linear solutions for wide relu networks — A Shevchenko, V Kungurtsev, M Mondelli. Journal of Machine Learning Research 23 (130), 1-55

2021

• Stochastic Model Predictive Control, Iterated Function Systems, and Stability — V Kungurtsev, J Marecek, R Shorten. arXiv preprint arXiv:2112.08138

• Iteration Complexity of a Fixed-Stepsize — F Facchinei, V Kungurtsev, L Lampariello. Numerical Analysis and Optimization: NAO-V, Muscat, Oman, January 2020, 109

• A zeroth order method for stochastic weakly convex optimization — V Kungurtsev, F Rinaldi. Computational Optimization and Applications 80 (3), 731-753

• Randomized algorithms for monotone submodular function maximization on the integer lattice — A Schiabel, V Kungurtsev, J Marecek. arXiv preprint arXiv:2111.10175

• Line-search and trust-region equations for a primal-dual interior method for nonlinear optimization — PE Gill, V Kungurtsev, DP Robinson. Center for Computational Mathematics Report Technical Report CCoM-21-4 …

• On the effect of perturbations, errors in first-order optimization methods with inertia and Hessian driven damping — H Attouch, J Fadili, V Kungurtsev. arXiv preprint arXiv:2106.16159

• 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

• Complexity iteration analysis for strongly convex multi-objective optimization using a Newton path-following procedure: E. Bergou et al. — EH Bergou, Y Diouane, V Kungurtsev. Optimization Letters 15 (4), 1215-1227

• Asynchronous optimization methods for efficient training of deep neural networks with guarantees — V Kungurtsev, M Egan, B Chatterjee, D Alistarh. Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8209-8216

• Elastic consistency: A practical consistency model for distributed stochastic gradient descent — G Nadiradze, I Markov, B Chatterjee, V Kungurtsev, D Alistarh. Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9037-9045

• 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

• Time-varying semidefinite programming: Geometry of the trajectory of solutions — A Bellon, D Henrion, V Kungurtsev, J Marecek. arXiv preprint arXiv:2104.05445

• Decentralized langevin dynamics over a directed graph — A Kolesov, V Kungurtsev. arXiv preprint arXiv:2103.05444

• A nonmonotone matrix-free algorithm for nonlinear equality-constrained least-squares problems — EH Bergou, Y Diouane, V Kungurtsev, CW Royer. SIAM Journal on Scientific Computing 43 (5), S743-S766

2020

• A two-step pre-processing for semidefinite programming — V Kungurtsev, J Marecek. 2020 59th IEEE Conference on Decision and Control (CDC), 384-389

• Asynchronous parallel algorithms for nonconvex optimization — L Cannelli, F Facchinei, V Kungurtsev, G Scutari. Mathematical Programming 184 (1), 121-154

• 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

• Stochastic Gradient Langevin with Delayed Gradients — V Kungurtsev, B Chatterjee, D Alistarh. arXiv preprint arXiv:2006.07362

• 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

• Fast sensitivity-based economic model predictive control for degenerate systems — E Suwartadi, V Kungurtsev, J Jäschke. Journal of Process Control 88, 54-62

• Zero Order Stochastic Weakly Convex Composite Optimization — V Kungurtsev, F Rinaldi. arXiv preprint arXiv:2002.08083

• Lifted weight learning of markov logic networks (revisited one more time) — O Kuzelka, V Kungurtsev, Y Wang. International Conference on Probabilistic Graphical Models, 269-280

• Iteration complexity of a fixed-stepsize SQP method for nonconvex optimization with convex constraints — F Facchinei, V Kungurtsev, L Lampariello, G Scutari. Numerical analysis and optimization, 109-120

• Decentralized langevin dynamics — V Kungurtsev. arXiv preprint arXiv:2001.00665

• Second-order guarantees of distributed gradient algorithms — A Daneshmand, G Scutari, V Kungurtsev. SIAM Journal on Optimization 30 (4), 3029-3068

• A shifted primal-dual penalty-barrier method for nonlinear optimization — PE Gill, V Kungurtsev, DP Robinson. SIAM Journal on Optimization 30 (2), 1067-1093

• Reinforcement learning based on real-time iteration NMPC — M Zanon, V Kungurtsev, S Gros. ifac-Papersonline 53 (2), 5213-5218

• Convergence rate for diminishing stepsize methods in nonconvex constrained optimization via ghost penalties — F Facchinei, V Kungurtsev, L Lampariello, G Scutari. ATTI DELLA ACCADEMIA PELORITANA DEI PERICOLANTI, CLASSE DI SCIENZE FISICHE …

2019

• Lifted weight learning of markov logic networks revisited — O Kuzelka, V Kungurtsev. The 22nd International Conference on Artificial Intelligence and Statistics …

2018

• A Comparison of Nonsmooth, Nonconvex, Constrained Optimization Solvers for the Design of Time-Delay Compensators — V Kungurtsev, T Mitchell, T Vyhlidal. arXiv preprint arXiv:1812.11630

• Second-order guarantees of gradient algorithms over networks — A Daneshmand, G Scutari, V Kungurtsev. 2018 56th Annual Allerton Conference on Communication, Control, and …

• 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

• Algorithms for solving optimization problems arising from deep neural net models: smooth problems — V Kungurtsev, T Pevny. arXiv preprint arXiv:1807.00172

2017

• Input shaper optimization with a constraint on the spectrum distribution — V Kungurtsev, D Pilbauer, T Vyhlídal, M Hromčík, W Michiels. IFAC-PapersOnLine 50 (1), 13324-13329

• Capacity sensitivity in additive non-gaussian noise channels — M Egan, SM Perlaza, V Kungurtsev. 2017 IEEE International Symposium on Information Theory (ISIT), 416-420

• A stabilized SQP method: superlinear convergence — PE Gill, V Kungurtsev, DP Robinson. Mathematical Programming 163 (1), 369-410

• An SL/QP Algorithm for Minimizing the Spectral Abscissa of Time Delay Systems — V Kungurtsev, W Michiels, M Diehl. Time Delay Systems: Theory, Numerics, Applications, and Experiments, 33-45

• Asynchronous parallel nonconvex large-scale optimization — L Cannelli, F Facchinei, V Kungurtsev, G Scutari. 2017 IEEE International Conference on Acoustics, Speech and Signal …

• Sensitivity-based economic NMPC with a path-following approach — E Suwartadi, V Kungurtsev, J Jäschke. Processes 5 (1), 8

• A predictor-corrector path-following algorithm for dual-degenerate parametric optimization problems — V Kungurtsev, J Jaschke. SIAM Journal on Optimization 27 (1), 538-564

• A stabilized SQP method: global convergence — PE Gill, V Kungurtsev, DP Robinson. IMA Journal of Numerical Analysis 37 (1), 407-443

2016

• Parallel asynchronous lock-free algorithms for nonconvex big-data optimization — L Cannelli, G Scutari, F Facchinei, V Kungurtsev. 2016 50th Asilomar Conference on Signals, Systems and Computers, 1009-1013

• Distance-to-solution estimates for optimization problems with constraints in standard form — PE Gill, V Kungurtsev, DP Robinson. Center for Computational Mathematics Report CCoM, 16-01

• TECHNICAL REPORT, DEPARTMENT OF CHEMICAL ENGINEERING, NTNU 23.03. 2016 — V KUNGURTSEV, J JÄSCHKE. CONVERGENCE

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

2014

• Sequential quadratic programming methods for parametric nonlinear optimization — V Kungurtsev, M Diehl. Computational Optimization and Applications 59 (3), 475-509

• An Inequality Constrained SL/QP Method for Minimizing the Spectral Abscissa — V Kungurtsev, W Michiels, M Diehl. arXiv preprint arXiv:1411.2362

• Flexible selective parallel algorithms for big data optimization — A Daneshmand, F Facchinei, V Kungurtsev, G Scutari. 2014 48th Asilomar conference on signals, systems and computers, 3-7

• Linear convergence of distributed multiple shooting — V Kungurtsev, A Kozma, M Diehl. 2014 European Control Conference (ECC), 2874-2879

2013

• 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

• Second-derivative sequential quadratic programming methods for nonlinear optimization — V Kungurtsev. University of California, San Diego

2012

• Negative Curvature and Second-order optimality for regularized SQP — P Gill, V Kungurtsev, D Robinson. arXiv preprint arXiv:1205.2304

2011

• Numerical bifurcation analysis of conformal formulations of the Einstein constraints — M Holst, V Kungurtsev. Physical Review D—Particles, Fields, Gravitation, and Cosmology 84 (12), 124038

2009

• Disambiguation of the DBLP Database — M Alvisio, C Nathe, C Kim, V Kungurtsev. 1

Undated

• Federated Sinkhorn: Communication, Performance, and Privacy for Distributed Entropic Optimal Transport — J Kulcsar, V Kungurtsev, G Korpas, G Giaconi, W Shoosmith. Performance, and Privacy for Distributed Entropic Optimal Transport

• COAP 2024 best paper prize: paper of Y. Diouane, V. Kungurtsev, F. Rinaldi, and D. Zeffiro — F Rinaldi

• AI for Enhancing Operations Research of Agriculture and Energy — M Kimiaei, A Kumar, V Kungurtsev

• Machine Learning Algorithms for Assisting Solvers for Constraint Satisfaction Problems — M Kimiaei, V Kungurtsev

• Machine Learning Algorithms for Assisting Solvers for Decision Optimization Problems — M Kimiaei, V Kungurtsev

• Hybrid Methods for global optimization of large-scale polynomials — J Aspman, G Bareilles, V Kungurtsev, J Mareček, M Takáč

• Supplementary Material: Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents — Y Jia, S Vahidian, J Sun, J Zhang, V Kungurtsev, NZ Gong, Y Chen

• Complexity iteration analysis for strongly convex — EH Bergou, Y Diouane, V Kungurtsev

• Local SGD Meets Asynchrony — B Chatterjee, V Kungurtsev, D Alistarh