The cycle count statistics
Holder： Shunjia Jin（Southeast University/Carnegie Mellon University）
Time：2025-05-19 14:00-15:00
Location：WANG Xuan Lecture Theater，Zhi Hua Building-101
Abstract:
Despite recent progress, AI still struggles on advanced mathematics. We consider a difficult open problem: How to derive a Computationally Efficient Equivalent Form (CEEF) for the cycle count statistic? The CEEF problem does not have known general solutions, and requires delicate combinatorics and tedious calculations. Such a task is hard to accomplish by humans but is an ideal example where AI can be very helpful. We solve the problem by combining a novel approach we propose and the powerful coding skills of AI. Our results use delicate graph theory and contain new formulas for general cases that have not been discovered before. We find that, while AI is unable to solve the problem all by itself, it is able to solve it if we provide it with a clear strategy, a step-by-step guidance and carefully written prompts. For simplicity, we focus our study on DeepSeek-R1 but we also investigate other AI approaches.
About the Speaker:
Jiashun Jin is Professor in Statistics & Data Science and Affiliated Professor in Machine Learning at Carnegie Mellon University.He is also the dean of the School of Statistics and Data Science at Southeast University.His earlier work was on the analysis of Rare/Weak signals in big data, focusing on the development of (Tukey's) Higher Criticism and practical False Discovery Rate (PDR) controlling methods.His more recent interest is on the analysis of complex network and text data,where he has led a team collecting a large-scale data set on statistical three Editor a bication biallusio apers anin the las, lin hascounteds Invited Review papers. Jin is an elected IMS fellow and an elected ASA fellow, and he has delivered the highly selective IMS Medallion Lecture in 2015 and IMS AAS (Annals of Applied Statistics) Lecture in 2016. He was also a recipient of the NSF CAREER award and the IMS Tweedie Award. He has served as Associate Editor for several statistical journals and he is currently severing IMS as the IMS Treasurer. Beyond his academic career, Jin has also gained valuable experience in industry by doing research at Two-Sigma Investments and Google LLC.
Your participation is warmly welcomed!
欢迎扫码关注北大统计科学中心公众号，了解更多讲座信息!
