发表刊物：Applied Intelligence

摘要：In the paper, we propose a variant of Variational Autoencoder (VAE) for sequence generation task, called SeqVAE, which is a combination of recurrent VAE and policy gradient in reinforcement learning. The goal of SeqVAE is to reduce the deviation of the optimization goal of VAE, which we achieved by adding the policy-gradient loss to SeqVAE. In the paper, we give two ways to calculate the policy-gradient loss, one is from SeqGAN and the other is proposed by us. In the experiments on them, our proposed method is better than all baselines, and experiments show that SeqVAE can alleviate the ......

论文类型：期刊论文

第一作者：高亭

合写作者：丁凡彧

通讯作者：崔毅东

文献类型：J

ISSN号：1573-7497

是否译文：否

发表时间：2021-04-21

收录刊物：SCI

发布期刊链接：https://doi.org/10.1007/s10489-021-02374-7