I am Ruomin Huang (黄若民 in Chinese), a 2nd-year CS Ph.D. student at Duke University. I am very 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 interested in mechanisms physics of transformers.
* denotes equal contribution.
Task Descriptors Help Transformers Learn Linear Models In-Context
Ruomin Huang and Rong Ge
ICML 2024 Workshop on In-Context Learning
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
Roy Xie, Junlin Wang, Ruomin Huang, Minxing Zhang, Rong Ge, Jian Pei, Neil Gong, Bhuwan Dhingra
EMNLP 2024
Randomized Greedy Algorithms and Composable Coreset for k-Center Clustering with Outliers
Hu Ding, Ruomin Huang, Kai Liu, Haikuo Yu, Zixiu Wang
Preprint
Coresets for Wasserstein Distributionally Robust Optimization Problems
Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding
NeurIPS 2022 (spotlight)
Coresets for Relational Data and The Applications
Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding
NeurIPS 2022 (spotlight)
A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang*, Ruomin Huang*, Wenjie Liu*, Nikolaos M. Freris, Hu Ding
ICML 2021 (spotlight)
I am open to discussions.