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2020 – today
- 2024
[c6]Roy Xie, Junlin Wang, Ruomin Huang, Minxing Zhang, Rong Ge, Jian Pei, Neil Gong, Bhuwan Dhingra:
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods. EMNLP 2024: 8671-8689- [c5]Weichen Lin, Jiaxiang Chen, Ruomin Huang, Hu Ding:
An Effective Dynamic Gradient Calibration Method for Continual Learning. ICML 2024 - [i6]Roy Xie, Junlin Wang, Ruomin Huang, Minxing Zhang, Rong Ge, Jian Pei, Neil Zhenqiang Gong, Bhuwan Dhingra:
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods. CoRR abs/2406.15968 (2024) - [i5]Weichen Lin, Jiaxiang Chen, Ruomin Huang, Hu Ding:
An Effective Dynamic Gradient Calibration Method for Continual Learning. CoRR abs/2407.20956 (2024) - 2023
- [c4]Ruomin Huang, Yukun Feng, Yumin Cao:
The Impact of the Volume-Based Procurement Policy on Organizational Innovation Investment: Evidence from Chinese A-share Pharmaceutical Firms. DMI 2023: 311-323 - [i4]Hu Ding, Ruomin Huang, Kai Liu, Haikuo Yu, Zixiu Wang:
Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers. CoRR abs/2301.02814 (2023) - 2022
- [c3]Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding:
Coresets for Relational Data and The Applications. NeurIPS 2022 - [c2]Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding:
Coresets for Wasserstein Distributionally Robust Optimization Problems. NeurIPS 2022 - [i3]Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding:
Coresets for Relational Data and The Applications. CoRR abs/2210.04249 (2022) - [i2]Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding:
Coresets for Wasserstein Distributionally Robust Optimization Problems. CoRR abs/2210.04260 (2022) - 2021
- [c1]Jiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos M. Freris, Hu Ding:
A Novel Sequential Coreset Method for Gradient Descent Algorithms. ICML 2021: 4412-4422 - [i1]Jiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos M. Freris, Hu Ding:
A Novel Sequential Coreset Method for Gradient Descent Algorithms. CoRR abs/2112.02504 (2021)
Coauthor Index
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