Author: Lai Zhaorong

Publisher: College of Information Science and Technology  

Date: July 12, 2024

The Mathematics Department of the School of Information Science and Technology at Jinan University has made significant strides in the field of machine learning, with two papers accepted at the prestigious International Conference on Machine Learning (ICML2024), a CCF Class A conference. The papers are titled:

1. Autonomous Sparse Mean CVaR Portfolio Optimization  

   - First Author: Lin Yizun (Mathematics Department)  

   - Second Author: Zhang Yangyu (Peking University, 2023 graduate)  

   - Third Author: Lai Zhaorong (Mathematics Department, Corresponding Author)  

   - Fourth Author: Li Cheng (Mathematics Department, 2023 doctoral student)  

2. Invariant Risk Minimization Is A Total Variation Model  

   - First Author: Lai Zhaorong  

   - Second Author: Wang Weiwen (Mathematics Department, Corresponding Author)  

The ICML conference, recognized internationally as one of the leading events in machine learning, received a total of 9,473 submissions, with only 2,609 papers accepted, yielding an acceptance rate of approximately 27.5%. The 41st iteration of the conference will take place in Vienna, Austria, from July 21 to July 27, 2024.

The research conducted by Lin Yizun, Wang Weiwen, and Lai Zhaorong is supported by the Guangdong Provincial Quantitative Finance Big Data Engineering Technology Research Center and various funding initiatives, including:

- National Natural Science Foundation General Project (62176103)

- Guangdong Provincial Basic and Applied Basic Research Fund Project (2021A1515110541)

- Guangzhou Science and Technology Plan Projects (2024A04J9896, 2024A04J3940, 2024A04J4225)

- Central University Basic Research Business Expenses (21623341)

The acceptance of these papers not only highlights the advancing research capabilities and quality of training for young faculty at Jinan University but also underscores the institution's commitment to becoming a high-level university in the field.