I am Ruomin Huang (黄若民 in Chinese), a first-year CS Ph.D. student at Duke University. I am fortunate to be advised by Prof. Rong Ge. Previously I received M.S. in Data Science and B.S. in Computational Mathematics from USTC, where I worked with Prof. Hu Ding.
Previously I worked on the algorithmic aspect of ML. Now I am generally interested in ML theory, especially DL theory. Here are some interesting topics.
* denotes equal contribution.
Hu Ding, Ruomin Huang, Kai Liu, Haikuo Yu, Zixiu Wang, Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers, submitted for publication.
Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding, Coresets for Wasserstein Distributionally Robust Optimization Problems, NeurIPS 2022 (spotlight).
Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding, Coresets for Relational Data and The Applications, NeurIPS 2022 (spotlight).
Jiawei Huang*, Ruomin Huang*, Wenjie Liu*, Nikolaos M. Freris, Hu Ding, A Novel Sequential Coreset Method for Gradient Descent Algorithms, ICML 2021.
I am open to discussions.