| Hierarchical attention networks for document classification Z Yang, D Yang, C Dyer, X He, A Smola, E Hovy Proceedings of the 2016 conference of the North American chapter of the …, 2016 | 4115 | 2016 |
| Stacked attention networks for image question answering Z Yang, X He, J Gao, L Deng, A Smola Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1685 | 2016 |
| Toward controlled generation of text Z Hu, Z Yang, X Liang, R Salakhutdinov, EP Xing arXiv preprint arXiv:1703.00955, 2017 | 908* | 2017 |
| Improved variational autoencoders for text modeling using dilated convolutions Z Yang, Z Hu, R Salakhutdinov, T Berg-Kirkpatrick International conference on machine learning, 3881-3890, 2017 | 325 | 2017 |
| Deep fried convnets Z Yang, M Moczulski, M Denil, N De Freitas, A Smola, L Song, Z Wang Proceedings of the IEEE international conference on computer vision, 1476-1483, 2015 | 306 | 2015 |
| Unsupervised text style transfer using language models as discriminators Z Yang, Z Hu, C Dyer, EP Xing, T Berg-Kirkpatrick Advances in Neural Information Processing Systems 31, 2018 | 206 | 2018 |
| Parameter server for distributed machine learning M Li, L Zhou, Z Yang, A Li, F Xia, DG Andersen, A Smola Big learning NIPS workshop 6, 2, 2013 | 194 | 2013 |
| Controllable text generation. arXiv preprint Z Hu, Z Yang, X Liang, R Salakhutdinov, EP Xing arXiv preprint arXiv:1703.00955 7, 2017 | 131 | 2017 |
| A la carte–learning fast kernels Z Yang, A Wilson, A Smola, L Song Artificial Intelligence and Statistics, 1098-1106, 2015 | 130 | 2015 |
| On unifying deep generative models Z Hu, Z Yang, R Salakhutdinov, EP Xing arXiv preprint arXiv:1706.00550, 2017 | 121 | 2017 |
| Mixtext: Linguistically-informed interpolation of hidden space for semi-supervised text classification J Chen, Z Yang, D Yang arXiv preprint arXiv:2004.12239, 2020 | 115 | 2020 |
| Multimodal intelligence: Representation learning, information fusion, and applications C Zhang, Z Yang, X He, L Deng IEEE Journal of Selected Topics in Signal Processing 14 (3), 478-493, 2020 | 106 | 2020 |
| Reference-aware language models Z Yang, P Blunsom, C Dyer, W Ling arXiv preprint arXiv:1611.01628, 2016 | 85 | 2016 |
| Deep generative models with learnable knowledge constraints Z Hu, Z Yang, RR Salakhutdinov, L Qin, X Liang, H Dong, EP Xing Advances in Neural Information Processing Systems 31, 2018 | 65 | 2018 |
| Deep neural networks with massive learned knowledge Z Hu, Z Yang, R Salakhutdinov, E Xing Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 65 | 2016 |
| Security adoption and influence of cyber-insurance markets in heterogeneous networks Z Yang, JCS Lui Performance Evaluation 74, 1-17, 2014 | 55 | 2014 |
| Texar: A modularized, versatile, and extensible toolkit for text generation Z Hu, H Shi, B Tan, W Wang, Z Yang, T Zhao, J He, L Qin, D Wang, X Ma, ... arXiv preprint arXiv:1809.00794, 2018 | 53 | 2018 |
| Neural machine translation with recurrent attention modeling Z Yang, Z Hu, Y Deng, C Dyer, A Smola arXiv preprint arXiv:1607.05108, 2016 | 53 | 2016 |
| Let’s make your request more persuasive: Modeling persuasive strategies via semi-supervised neural nets on crowdfunding platforms D Yang, J Chen, Z Yang, D Jurafsky, E Hovy Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 36 | 2019 |
| The economics of the cloud: price competition and congestion J Anselmi, D Ardagna, JCS Lui, A Wierman, Y Xu, Z Yang ACM SIGMETRICS Performance Evaluation Review 41 (4), 47-49, 2014 | 33 | 2014 |
Zhiting HuAssistant Professor at UC San DiegoVerified email at ucsd.edu
