2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models
UAI 2020poster
Although with progress in introducing auxiliary amortized inference models, learning discrete latent variable models is still challenging. In this paper, we show that the annoying difficulty of obtaining reliable stochastic gradients for the inference model and the drawback of indirectly optimizing…