We release StatsMLlib that develops concentration of measure, metric entropy and chaining, empirical processes, Rademacher complexity, random matrix theory, and finite-sample learning guarantees as formal mathematics in Lean 4. Together, these results provide a unified foundation for probability, statistics, and machine learning, with every proof checked by the Lean 4 kernel.
Organizers:
Fanghui Liu, Jason D. Lee, Peter Bartlett, Weijie Su, Taiji Suzuki, Yuekai Sun, Aleksandar Mijatović, Sho Sonoda
Contributors:
Yuanhe Zhang, Sho Sonoda, Kei Tsukamoto, Kazumi Kasaura, Naoto Onda, Yuma Mizuno, and Kevin Han Huang, and Your name here
See more details on https:statsmllib.github.io
