(26) Oren Mangoubi and Nisheeth K Vishnoi.  Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers.  In International Conference on Learning Representations (ICLR), 2024.  (31% acceptance rate)

(25) Oren Mangoubi and Nisheeth K Vishnoi.  Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk.  In Neural Information Processing Systems (NeurIPS), 2023. (26% acceptance rate)

(24)  Oren Mangoubi and Nisheeth K Vishnoi. Private  Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. In Conference on Learning Theory (COLT) , 2023.  (35% acceptance rate)

(23)  Vincent Filardi, Allen Cheung, Ruba Khan, Oren Mangoubi, Majid Moradikia, Seyed (Reza) Zekavat, Brian Wilson, Radwin Askari, Douglas Petkie. Data-Driven Soil Water Content Estimation at Multiple Depths Using SFCW GPR.  In IEEE Opportunity Research Scholars Symposium (ORSS), 2023.

(22)   Oren Mangoubi and Nisheeth K Vishnoi.  Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion.   In Advances in Neural Information Processing Systems (NeurIPS), 2022.  (26% acceptance rate)

(21)   Oren Mangoubi and Nisheeth K Vishnoi.   Sampling from Log-Concave Distributions with Infinity-Distance Guarantees.   In Advances in Neural Information Processing Systems (NeurIPS), 2022. (26% acceptance rate)

(20)   Eric Vertina, N. Aaron Deskins, Emily Sutherland, Oren Mangoubi.  Predicting MXene Properties via Machine Learning.   In IEEE International Conference on Machine Learning and Applications (ICMLA), 2022. 

(19) Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, and Nisheeth K Vishnoi. A Convergent and Dimension-Independent Min-Max Optimization Algorithm, In  International Conference on Machine Learning  (ICML), 2022, with Oral Presentation (2% acceptance rate for oral)    (see also blog post)

(18) Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, and Nisheeth K Vishnoi.  Private Matrix Approximation and Geometry of Unitary Orbits, In Conference on Learning Theory (COLT), 2022.  (33% acceptance rate)

(17) Oren Mangoubi and Nisheeth K Vishnoi. Greedy Adversarial Equilibrium: An Efficient Alternative to Nonconvex-Nonconcave Min-Max Optimization, In ACM Symposium on Theory of Computing (STOC), 2021.  (28% acceptance rate)         (see also blog post)

(16)  Oren Mangoubi and Aaron Smith. Mixing of Hamiltonian Monte Carlo on Strongly Logconcave Distributions: Continuous Dynamics.  Annals of Applied Probability, 2021.

(15)  Xin Zhang,  Yanhua Li,  Xun Zhou,  Oren Mangoubi,  Ziming Zhang,  Vincent Filardi,  Jun Luo .  DAC-ML:  Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction.  Accepted as a regular paper in IEEE International Conference on Data Mining (ICDM), 2021.  (9.9% acceptance rate for regular papers)

(14) Shijian Li, Oren Mangoubi, Lijie Xu and Tian Guo.   Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning,   In International Conference on Distributed Computing Systems (ICDCS), 2021.  (20% acceptance rate)

(13) Oren Mangoubi, Natesh S Pillai, and Aaron Smith. Simple Conditions for Metastability of Continuous Markov Chains. Journal of Applied Probability, 2021. 

(12) Holden Lee, Oren Mangoubi, and Nisheeth K Vishnoi. Online sampling from log-concave distributions. In Advances in Neural Information Processing Systems (NeurIPS), 2019. (21% acceptance rate)

(11) Oren Mangoubi and Nisheeth K Vishnoi. Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk, In IEEE Symposium on Foundations of Computer Science (FOCS), 2019. (29% acceptance rate)

(10) Oren Mangoubi and Nisheeth K Vishnoi. Nonconvex sampling with the Metropolis-adjusted Langevin algorithm, In Conference on Learning Theory (COLT), 2019. (30% acceptance rate)

(9) Oren Mangoubi and Aaron Smith. Mixing of Hamiltonian Monte Carlo on Strongly Logconcave distributions 2: Numerical Integrators. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. (32% acceptance rate)

(8) Oren Mangoubi and Nisheeth K. Vishnoi. Dimensionally tight bounds for second-order Hamiltonian Monte Carlo. In Advances in Neural Information Processing Systems (NeurIPS), 2018. (21% acceptance rate)

(7) Oren Mangoubi and Aaron Smith. Rapid mixing of geodesic walks on manifolds with positive curvature.  Annals of Applied Probability, 28(4): 2501-2543, 2018.

(6) Oren Mangoubi and Nisheeth K. Vishnoi. Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. In Conference on Learning Theory (COLT), pages 1086-1124. Proceedings of Machine Learning Research (PMLR), 2018. (27% acceptance rate)

(5) Oren Mangoubi. Strategic behavior in multiple-period financial markets. In Optimization theory and related topics, volume 568 of Contemporary Mathematics, pages 191-212. American Mathematical Society, Providence, RI, 2012.

(4) Reut Avni, Oren Mangoubi, Rangeet Bhattacharyya, Hadassa Degani, and Lucio Frydman. Magnetization transfer magic-angle-spinning z-spectroscopy of excised tissues. Journal of Magnetic Resonance, 199(1):1-9, 2009.

(3) Oren Mangoubi, Shaoshuai Mou, Ji Liu, and A Stephen Morse. Towards optimal convex combination rules for gossiping. In American Control Conference (ACC), pages 1261-1265. IEEE, 2013.

(2) Edwin A Marengo and Oren Mangoubi. Compressive through-focus wavefield imaging. In IS&T/SPIE Electronic Imaging, pages 1-9. International Society for Optics and Photonics, 2011.

(1) Oren Mangoubi and Edwin A Marengo. Compressive through-focus imaging. In Progress in Electromagnetic Research Symposium (PIERS) Proceedings, pages 942-946, 2010.