| 2025 | ICLR | Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions. | Peiyao Lai, Oren Mangoubi |
| 2025 | ICML | Efficient Diffusion Models for Symmetric Manifolds. | Oren Mangoubi, Neil He, Nisheeth K. Vishnoi |
| 2024 | ICLR | Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2023 | COLT | Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2022 | COLT | Private Matrix Approximation and Geometry of Unitary Orbits. | Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi |
| 2022 | ICML | A Convergent and Dimension-Independent Min-Max Optimization Algorithm. | Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi |
| 2022 | ICMLA | Predicting MXene Properties via Machine Learning. | Eric W. Vertina, N. Aaron Deskins, Emily Sutherland, Oren Mangoubi |
| 2021 | ICDCS | Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning. | Shijian Li, Oren Mangoubi, Lijie Xu, Tian Guo |
| 2021 | ICDM | DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. | Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, Jun Luo |
| 2021 | STOC | Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2019 | AISTATS | Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators. | Oren Mangoubi, Aaron Smith |
| 2019 | COLT | Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2019 | FOCS | Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2018 | COLT | Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. | Oren Mangoubi, Nisheeth K. Vishnoi |