| Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions: Continuous dynamics O Mangoubi, A Smith The Annals of Applied Probability 31 (5), 2019-2045, 2021 | 128 | 2021 |
| Dimensionally tight bounds for second-order Hamiltonian Monte Carlo O Mangoubi, N Vishnoi Advances in neural information processing systems 31, 2018 | 76 | 2018 |
| Nonconvex sampling with the Metropolis-adjusted Langevin algorithm O Mangoubi, NK Vishnoi Conference on learning theory, 2259-2293, 2019 | 43 | 2019 |
| Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities? O Mangoubi, NS Pillai, A Smith arXiv preprint arXiv:1808.03230, 2018 | 39 | 2018 |
| Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators O Mangoubi, A Smith The 22nd international conference on artificial intelligence and statistics …, 2019 | 33 | 2019 |
| Rapid mixing of geodesic walks on manifolds with positive curvature O Mangoubi, A Smith The Annals of Applied Probability 28 (4), 2501-2543, 2018 | 30 | 2018 |
| Faster polytope rounding, sampling, and volume computation via a sub-linear ball walk O Mangoubi, NK Vishnoi 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS …, 2019 | 27 | 2019 |
| Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization O Mangoubi, NK Vishnoi Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 26 | 2021 |
| Sampling from log-concave distributions with infinity-distance guarantees O Mangoubi, N Vishnoi Advances in neural information processing systems 35, 12633-12646, 2022 | 20 | 2022 |
| Sync-switch: Hybrid parameter synchronization for distributed deep learning S Li, O Mangoubi, L Xu, T Guo 2021 IEEE 41st International Conference on Distributed Computing Systems …, 2021 | 19 | 2021 |
| Convex optimization with unbounded nonconvex oracles using simulated annealing O Mangoubi, NK Vishnoi Conference On Learning Theory, 1086-1124, 2018 | 15 | 2018 |
| Magnetization transfer magic-angle-spinning z-spectroscopy of excised tissues R Avni, O Mangoubi, R Bhattacharyya, H Degani, L Frydman Journal of Magnetic Resonance 199 (1), 1-9, 2009 | 15 | 2009 |
| Re-analyze Gauss: Bounds for private matrix approximation via Dyson Brownian motion O Mangoubi, N Vishnoi Advances in Neural Information Processing Systems 35, 38585-38599, 2022 | 14 | 2022 |
| Dac-ml: domain adaptable continuous meta-learning for urban dynamics prediction X Zhang, Y Li, X Zhou, O Mangoubi, Z Zhang, V Filardi, J Luo 2021 IEEE International Conference on Data Mining (ICDM), 906-915, 2021 | 9 | 2021 |
| Towards optimal convex combination rules for gossiping O Mangoubi, S Mou, J Liu, AS Morse 2013 American Control Conference, 1261-1265, 2013 | 9 | 2013 |
| Data-driven soil water content estimation at multiple depths using SFCW GPR V Filardi, A Cheung, R Khan, O Mangoubi, M Moradikia, SR Zekavat, ... 2023 IEEE International Opportunity Research Scholars Symposium (ORSS), 86-90, 2023 | 8 | 2023 |
| Private covariance approximation and eigenvalue-gap bounds for complex gaussian perturbations O Mangoubi, NK Vishnoi The Thirty Sixth Annual Conference on Learning Theory, 1522-1587, 2023 | 7 | 2023 |
| A second-order equilibrium in nonconvex-nonconcave min-max optimization: Existence and algorithm O Mangoubi, NK Vishnoi arXiv preprint arXiv:2006.12363, 2020 | 6 | 2020 |
| Online sampling from log-concave distributions H Lee, O Mangoubi, N Vishnoi Advances in Neural Information Processing Systems 32, 2019 | 6 | 2019 |
| Advancing precision agriculture: Machine learning-enhanced GPR analysis for root-zone soil moisture assessment in mega farms H Namdari, M Moradikia, S Zekavat, R Askari, O Mangoubi, D Petkie IEEE Transactions on AgriFood Electronics, 2024 | 5 | 2024 |
