Bayes Reading Group: Xi Wang [UMass Amherst]

Friday Feb 9, 2024, 11:00 AM → 12:00 PM America/New_York

3rd Floor Conference Room/3-Flatiron Institute (162 5th Avenue)

Discussion Lead: Xi Wang [UMass Amherst]

Topic: Joint control variate for faster black-box variational inference

Link: https://arxiv.org/abs/2210.07290

Abstract: Black-box variational inference performance is sometimes hindered by the use of gradient estimators with high variance. This variance comes from two sources of randomness: Data subsampling and Monte Carlo sampling. While existing control variates only address Monte Carlo noise, and incremental gradient methods typically only address data subsampling, we propose a new "joint" control variate that jointly reduces variance from both sources of noise. This significantly reduces gradient variance, leading to faster optimization in several applications.