Oren Mangoubi - RankMe

42 papers A* 16A 2C 2Journal 21Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Efficient Diffusion Models for Symmetric Manifolds. ICML Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
2025	J	`jnl`	Efficient Diffusion Models for Symmetric Manifolds. CoRR Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
2025	J	`jnl`	Private Low-Rank Approximation for Covariance Matrices, Dyson Brownian Motion, and Eigenvalue-Gap Bounds for Gaussian Perturbations. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2025	J	`jnl`	Private Low-Rank Approximation for Covariance Matrices, Dyson Brownian Motion, and Eigenvalue-Gap Bounds for Gaussian Perturbations. J. ACM Oren Mangoubi, Nisheeth K. Vishnoi
2025	A*	`conf`	Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions. ICLR Peiyao Lai, Oren Mangoubi
2024	A*	`conf`	Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. ICLR Oren Mangoubi, Nisheeth K. Vishnoi
2024	J	`jnl`	Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2024	J	`jnl`	Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions. CoRR Peiyao Lai, Oren Mangoubi
2023	A*	`conf`	Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. COLT Oren Mangoubi, Nisheeth K. Vishnoi
2023	J	`jnl`	Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2023	A*	`conf`	Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk. NeurIPS Oren Mangoubi, Nisheeth K. Vishnoi
2022	A*	`conf`	A Convergent and Dimension-Independent Min-Max Optimization Algorithm. ICML Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi
2022	J	`jnl`	Faster Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2022	C	`conf`	Predicting MXene Properties via Machine Learning. ICMLA Eric W. Vertina, N. Aaron Deskins, Emily Sutherland, Oren Mangoubi
2022	A*	`conf`	Private Matrix Approximation and Geometry of Unitary Orbits. COLT Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi
2022	J	`jnl`	Private Matrix Approximation and Geometry of Unitary Orbits. CoRR Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Guha Thakurta, Nisheeth K. Vishnoi
2022	A*	`conf`	Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion. NeurIPS Oren Mangoubi, Nisheeth K. Vishnoi
2022	J	`jnl`	Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2022	A*	`conf`	Sampling from Log-Concave Distributions with Infinity-Distance Guarantees. NeurIPS Oren Mangoubi, Nisheeth K. Vishnoi
2021	A*	`conf`	DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. ICDM Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, Jun Luo
2021	A*	`conf`	Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization. STOC Oren Mangoubi, Nisheeth K. Vishnoi
2021	J	`jnl`	Sampling from Log-Concave Distributions with Infinity-Distance Guarantees and Applications to Differentially Private Optimization. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2021	J	`jnl`	Simple conditions for metastability of continuous Markov chains. J. Appl. Probab. Oren Mangoubi, Natesh S. Pillai, Aaron Smith
2021	A	`conf`	Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning. ICDCS Shijian Li, Oren Mangoubi, Lijie Xu, Tian Guo
2021	J	`jnl`	Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning. CoRR Shijian Li, Oren Mangoubi, Lijie Xu, Tian Guo
2020	J	`jnl`	A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs. CoRR Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi
2020	J	`jnl`	A Second-order Equilibrium in Nonconvex-Nonconcave Min-max Optimization: Existence and Algorithm. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2019	A*	`conf`	Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk. FOCS Oren Mangoubi, Nisheeth K. Vishnoi
2019	J	`jnl`	Faster algorithms for polytope rounding, sampling, and volume computation via a sublinear "Ball Walk". CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2019	A	`conf`	Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators. AISTATS Oren Mangoubi, Aaron Smith
2019	A*	`conf`	Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. COLT Oren Mangoubi, Nisheeth K. Vishnoi
2019	J	`jnl`	Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2019	J	`jnl`	Online Sampling from Log-Concave Distributions. CoRR Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi
2019	A*	`conf`	Online sampling from log-concave distributions. NeurIPS Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi
2018	A*	`conf`	Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. COLT Oren Mangoubi, Nisheeth K. Vishnoi
2018	A*	`conf`	Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo. NeurIPS Oren Mangoubi, Nisheeth K. Vishnoi
2018	J	`jnl`	Dimensionally Tight Running Time Bounds for Second-Order Hamiltonian Monte Carlo. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2018	J	`jnl`	Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities? CoRR Oren Mangoubi, Natesh S. Pillai, Aaron Smith
2017	J	`jnl`	Convex Optimization with Nonconvex Oracles. CoRR Oren Mangoubi, Nisheeth K. Vishnoi
2016	J	`jnl`	Rapid Mixing of Geodesic Walks on Manifolds with Positive Curvature. CoRR Oren Mangoubi, Aaron Smith
2013	C	`conf`	Towards optimal convex combination rules for gossiping. ACC Oren Mangoubi, Shaoshuai Mou, Ji Liu, A. Stephen Morse
2011	—	`conf`	Compressive through-focus wavefield imaging. Computational Imaging Edwin A. Marengo, Oren Mangoubi