Long-Kai Huang

        Email: HLONGKAI at gmail dot com

I am a senior researcher in Machine Learning Group, Tencent AI Lab. Prior to that, I obtained my Ph.D. in SCSE at NTU, advised by Prof. Sinno Jialin Pan.  I received B.Eng. from Sun Yat-Sen University and did my undergraduate thesis with Prof. Wei-Shi Zheng.

I am interested in the generalization and transferability of machine learning models and focus on 1) transfer learning, 2) meta learning and 3) continual learning.

Recent Publications

* indicates equal contributions. Underlined authors are research interns mentored by me.     

Retaining Beneficial Information from Detrimental Data for Neural Network Repair

Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Jialin Pan

Advances in Neural Information Processing Systems (NeurIPS) 2023

Secure Out-of-Distribution Task Generalization with Energy-Based Models

Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei

Advances in Neural Information Processing Systems (NeurIPS) 2023

Concept-wise Fine-tuning Matters in Preventing Negative Transfer

Yunqiao Yang, Long-Kai Huang, Ying Wei

International Conference on Computer Vision (ICCV) 2023

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation

Shuang Zhou, Xiao Huang, Ninghao Liu, Huachi Zhou, Fu-Lai Chung, Long-Kai Huang

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2023

Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization [paper] [code]

             Long-Kai Huang, Ying Wei

             Advances in Neural Information Processing Systems (NeurIPS) 2022

Adversarial Task Up-sampling for Meta-learning [paper]

             Yichen Wu, Long-Kai Huang, Ying Wei

             Advances in Neural Information Processing Systems (NeurIPS) 2022

Frustratingly Easy Transferability Estimation [paper] [code]

Long-Kai Huang, Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei

International Conference on Machine Learning (ICML), 2022

    Improving Generalization in Meta-learning via Task Augmentation [paper] [code]

Huaxiu Yao*, Long-Kai Huang*, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li

International Conference on Machine Learning (ICML), 2021

   Communication-Efficient Distributed PCA by Riemannian Optimization [paper]

Long-Kai Huang and Sinno Jialin Pan

International Conference on Machine Learning (ICML), 2020