Zhiming Zhou

According to our database, Zhiming Zhou authored at least 19 papers between 2016 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation?

Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Sobolev Wasserstein GAN.

Minkai Xu, Zhiming Zhou, Guansong Lu, Jian Tang, Weinan Zhang, Yong Yu

CoRR, 2020

Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency.

Guansong Lu, Zhiming Zhou, Jian Shen, Cheng Chen, Weinan Zhang, Yong Yu

CoRR, 2020

Quality of Experience Evaluation for Streaming Video Using CGNN.

Zhiming Zhou, Yu Dong, Li Song, Rong Xie, Lin Li, Bing Zhou

Proceedings of the 2020 IEEE International Conference on Visual Communications and Image Processing, 2020

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck.

Yuxuan Song, Lantao Yu, Zhangjie Cao, Zhiming Zhou, Jian Shen, Shuo Shao, Weinan Zhang, Yong Yu

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Quantifying Exposure Bias for Neural Language Generation.

Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass

CoRR, 2019

Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs.

Zhiming Zhou, Jian Shen, Yuxuan Song, Weinan Zhang, Yong Yu

CoRR, 2019

Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence.

Yaoming Zhu, Juncheng Wan, Zhiming Zhou, Liheng Chen, Lin Qiu, Weinan Zhang, Xin Jiang, Yong Yu

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Lipschitz Generative Adversarial Nets.

Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang

Proceedings of the 36th International Conference on Machine Learning, 2019

AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods.

Zhiming Zhou, Qingru Zhang, Guansong Lu, Hongwei Wang, Weinan Zhang, Yong Yu

Proceedings of the 7th International Conference on Learning Representations, 2019

Guiding the One-to-One Mapping in CycleGAN via Optimal Transport.

Guansong Lu, Zhiming Zhou, Yuxuan Song, Kan Ren, Yong Yu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis.

Zhiming Zhou, Yuxuan Song, Lantao Yu, Yong Yu

CoRR, 2018

Learning to Design Games: Strategic Environments in Reinforcement Learning.

Haifeng Zhang, Jun Wang, Zhiming Zhou, Weinan Zhang, Yin Wen, Yong Yu, Wenxin Li

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Activation Maximization Generative Adversarial Nets.

Zhiming Zhou, Han Cai, Shu Rong, Yuxuan Song, Kan Ren, Weinan Zhang, Jun Wang, Yong Yu

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Face Transfer with Generative Adversarial Network.

Runze Xu, Zhiming Zhou, Weinan Zhang, Yong Yu

CoRR, 2017

Generative Adversarial Nets with Labeled Data by Activation Maximization.

Zhiming Zhou, Shu Rong, Han Cai, Weinan Zhang, Yong Yu, Jun Wang

CoRR, 2017

Learning to Design Games: Strategic Environments in Deep Reinforcement Learning.

Haifeng Zhang, Jun Wang, Zhiming Zhou, Weinan Zhang, Ying Wen, Yong Yu, Wenxin Li

CoRR, 2017

Unsupervised Diverse Colorization via Generative Adversarial Networks.

Yun Cao, Zhiming Zhou, Weinan Zhang, Yong Yu

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Sparse-as-possible SVBRDF acquisition.

Zhiming Zhou, Guojun Chen, Yue Dong, David P. Wipf, Yong Yu, John M. Snyder, Xin Tong

ACM Trans. Graph., 2016