70 citations · 82 across the 6 of their papers we have counts for
9 papers
Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion
Oren Mangoubi, Nisheeth K. Vishnoi
Given a symmetric matrix and a vector , we present new bounds on the Frobenius-distance utility of the Gaussian mechanism for approximating by a matrix whose spectrum is…
Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning
Shijian Li, Oren Mangoubi, Lijie Xu +1
Stochastic Gradient Descent (SGD) has become the de facto way to train deep neural networks in distributed clusters. A critical factor in determining the training throughput and mo…
Faster polytope rounding, sampling, and volume computation via a sublinear "Ball Walk"
Oren Mangoubi, Nisheeth K. Vishnoi
We study the problem of "isotropically rounding" a polytope , that is, computing a linear transformation which makes the uniform distribution on the polytope…
Nonconvex sampling with the Metropolis-adjusted Langevin algorithm
Oren Mangoubi, Nisheeth K. Vishnoi
The Langevin Markov chain algorithms are widely deployed methods to sample from distributions in challenging high-dimensional and non-convex statistics and machine learning applica…
Online Sampling from Log-Concave Distributions
Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi
Given a sequence of convex functions , we study the problem of sampling from the Gibbs distribution for each epoch in…
Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities?
Oren Mangoubi, Natesh S. Pillai, Aaron Smith
Hamiltonian Monte Carlo (HMC) is a very popular and generic collection of Markov chain Monte Carlo (MCMC) algorithms. One explanation for the popularity of HMC algorithms is their…