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math.PR2022
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms
Aniket Das, Dheeraj Nagaraj, Anant Raj
We consider stochastic approximations of sampling algorithms, such as Stochastic Gradient Langevin Dynamics (SGLD) and the Random Batch Method (RBM) for Interacting Particle Dynamc…
math.OC2022
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization
Aniket Das, Bernhard Schölkopf, Michael Muehlebach
We analyze the convergence rates of stochastic gradient algorithms for smooth finite-sum minimax optimization and show that, for many such algorithms, sampling the data points with…