Unsupervised Diverse Colorization via Generative Adversarial Networks Y Cao, Z Zhou, W Zhang, Y Yu ECML, 2017, 2017 | 220 | 2017 |
Activation Maximization Generative Adversarial Nets Z Zhou, H Cai, S Rong, Y Song, K Ren, W Zhang, Y Yu, J Wang ICLR, 2018, 2018 | 118 | 2018 |
Lipschitz Generative Adversarial Nets Z Zhou, J Liang, Y Song, L Yu, H Wang, W Zhang, Y Yu, Z Zhang ICML, 2019, 2019 | 116 | 2019 |
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods Z Zhou, Q Zhang, G Lu, H Wang, W Zhang, Y Yu ICLR, 2019, 2019 | 77 | 2019 |
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? T He, J Zhang, Z Zhou, J Glass EMNLP, 2021, 2021 | 67* | 2021 |
Sparse-as-Possible SVBRDF acquisition Z Zhou, G Chen, Y Dong, D Wipf, Y Yu, J Snyder, X Tong SIGGRAPH Asia - ACM Transactions on Graphics (TOG), 2016, 2016 | 55 | 2016 |
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence Z Yaoming, W Juncheng, Z Zhiming, C Liheng, Q Lin, Z Weinan, J Xin, ... SIGIR, 2019, 2019 | 36* | 2019 |
Guiding the One-to-one Mapping in CycleGAN via Optimal Transport G Lu, Z Zhou, Y Song, K Ren, Y Yu AAAI, 2019, 2018 | 29 | 2018 |
Learning to Design Games: Strategic Environments in Deep Reinforcement Learning H Zhang, J Wang, Z Zhou, W Zhang, Y Wen, Y Yu, W Li IJCAI, 2018, 2018 | 23* | 2018 |
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck Y Song, L Yu, Z Cao, Z Zhou, J Shen, S Shao, W Zhang, Y Yu ECAI, 2020, 2020 | 18 | 2020 |
Towards Generalized Implementation of Wasserstein Distance in GANs M Xu, Z Zhou, G Lu, J Tang, W Zhang, Y Yu AAAI, 2021, 2021 | 13 | 2021 |
Large-Scale Optimal Transport with Cycle-Consistency G Lu, Z Zhou, J Shen, C Chen, W Zhang, Y Yu Preprint, 2020, 2020 | 12* | 2020 |
Clustered Embedding Learning for Recommender Systems Y Chen, G Huzhang, A Zeng, Q Yu, H Sun, HY Li, J Li, Y Ni, H Yu, Z Zhou WWW, 2023, 2023 | 10 | 2023 |
Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs Z Zhou, J Shen, Y Song, W Zhang, Y Yu Preprint, 2019, 2019 | 2 | 2019 |
Residual Multi-Task Learner for Applied Ranking C Fu, K Wang, J Wu, Y Chen, G Huzhang, Y Ni, A Zeng, Z Zhou KDD, 2024, 2024 | | 2024 |
Learning Personalizable Clustered Embedding for Recommender Systems Y CHEN, G Huzhang, A ZENG, Q YU, HUI SUN, HYI LI, J LI, Y NI, HAN YU, ... ACM Transactions on Recommender Systems (TORS), 2024, 2024 | | 2024 |
Recurrent Temporal Revision Graph Networks Y Chen, A Zeng, G Huzhang, Q Yu, K Zhang, C Yuanpeng, K Wu, H Yu, ... NeurIPS, 2023, 2023 | | 2023 |