130 citations · 304 across the 10 of their papers we have counts for
5 papers · 1 filter
Optimal Robust Linear Regression in Nearly Linear Time
Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni +3
We study the problem of high-dimensional robust linear regression where a learner is given access to samples from the generative model (with $X…
An Efficient Sampling Algorithm for Non-smooth Composite Potentials
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright +1
We consider the problem of sampling from a density of the form , where is a smooth and strongly convex func…
Is There an Analog of Nesterov Acceleration for MCMC?
Yi-An Ma, Niladri Chatterji, Xiang Cheng +3
We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as optimization on the space of probability measures, with Kullback-Leibler (KL) divergence as the objective fu…
Sampling Can Be Faster Than Optimization
Yi-An Ma, Yuansi Chen, Chi Jin +2
Optimization algorithms and Monte Carlo sampling algorithms have provided the computational foundations for the rapid growth in applications of statistical machine learning in rece…
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma +2
We provide convergence guarantees in Wasserstein distance for a variety of variance-reduction methods: SAGA Langevin diffusion, SVRG Langevin diffusion and control-variate underdam…