Da Yu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
11
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | Scaling Laws for Differentially Private Language Models. | Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang |
| 2025 | IJCNLP | On Memorization of Large Language Models in Logical Reasoning. | Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar |
| 2024 | ICML | Differentially Private Synthetic Data via Foundation Model APIs 2: Text. | Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin |
| 2024 | ICML | Privacy-Preserving Instructions for Aligning Large Language Models. | Da Yu, Peter Kairouz, Sewoong Oh, Zheng Xu |
| 2023 | AISTATS | Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. | Huishuai Zhang, Da Yu, Yiping Lu, Di He |
| 2023 | ICLR | Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. | Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian |
| 2022 | ICLR | Differentially Private Fine-tuning of Language Models. | Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang |
| 2022 | KDD | Availability Attacks Create Shortcuts. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2021 | AAAI | How Does Data Augmentation Affect Privacy in Machine Learning? | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2021 | ICLR | Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. | Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu |
| 2021 | ICML | Large Scale Private Learning via Low-rank Reparametrization. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2020 | IJCAI | Gradient Perturbation is Underrated for Differentially Private Convex Optimization. | Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu |
| 2020 | SIGCOMM | Accuracy, Scalability, Coverage: A Practical Configuration Verifier on a Global WAN. | Fangdan Ye, Da Yu, Ennan Zhai, Hongqiang Harry Liu, Bingchuan Tian, Qiaobo Ye, Chunsheng Wang, Xin Wu, Tianchen Guo, Cheng Jin, Duncheng She, Qing Ma, Biao Cheng, Hui Xu, Ming Zhang, Zhiliang Wang, Rodrigo Fonseca |
| 2019 | NSDI | dShark: A General, Easy to Program and Scalable Framework for Analyzing In-network Packet Traces. | Da Yu, Yibo Zhu, Behnaz Arzani, Rodrigo Fonseca, Tianrong Zhang, Karl Deng, Lihua Yuan |
| 2019 | SIGCOMM | Safely and automatically updating in-network ACL configurations with intent language. | Bingchuan Tian, Xinyi Zhang, Ennan Zhai, Hongqiang Harry Liu, Qiaobo Ye, Chunsheng Wang, Xin Wu, Zhiming Ji, Yihong Sang, Ming Zhang, Da Yu, Chen Tian, Haitao Zheng, Ben Y. Zhao |
| 2014 | ACISP | CoChecker: Detecting Capability and Sensitive Data Leaks from Component Chains in Android. | Xingmin Cui, Da Yu, Patrick P. F. Chan, Lucas Chi Kwong Hui, Siu-Ming Yiu, Sihan Qing |
| 2010 | ICNC | A logistics demand forecasting model based on Grey neural network. | Fangzhong Qi, Da Yu, Bernhard Holtkamp |