39 citations · 75 across the 5 of their papers we have counts for
8 papers
Towards Generalized Implementation of Wasserstein Distance in GANs
Minkai Xu, Zhiming Zhou, Guansong Lu +3
Wasserstein GANs (WGANs), built upon the Kantorovich-Rubinstein (KR) duality of Wasserstein distance, is one of the most theoretically sound GAN models. However, in practice it doe…
Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency
Guansong Lu, Zhiming Zhou, Jian Shen +3
Recent advances in large-scale optimal transport have greatly extended its application scenarios in machine learning. However, existing methods either not explicitly learn the tran…
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Yuxuan Song, Lantao Yu, Zhangjie Cao +5
Domain adaptation aims to leverage the supervision signal of source domain to obtain an accurate model for target domain, where the labels are not available. To leverage and adapt…
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Yaoming Zhu, Juncheng Wan, Zhiming Zhou +5
Knowledge base is one of the main forms to represent information in a structured way. A knowledge base typically consists of Resource Description Frameworks (RDF) triples which des…
Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs
Zhiming Zhou, Jian Shen, Yuxuan Song +2
Lipschitz continuity recently becomes popular in generative adversarial networks (GANs). It was observed that the Lipschitz regularized discriminator leads to improved training sta…
Lipschitz Generative Adversarial Nets
Zhiming Zhou, Jiadong Liang, Yuxuan Song +5
In this paper, we study the convergence of generative adversarial networks (GANs) from the perspective of the informativeness of the gradient of the optimal discriminative function…