Training latent variable machine learning models using multi-sample objectives

摘要

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model. One of the methods includes, for each training observation: determining a plurality of latent variable value configurations, each latent variable value configuration being a combination of latent variable values that includes a respective value for each of the latent variables; determining, for each of the plurality of latent variable value configurations, a respective local learning signal that is minimally dependent on each of the other latent variable value configurations in the plurality of latent variable value configurations; determining an unbiased estimate of a gradient of the objective function using the local learning signals; and updating current values of the parameters of the machine learning model using the unbiased estimate of the gradient.