Machine Learning and Finance

Machine Learning and Finance

관련기사 바로가기

Nonconvex optimization, Stochastic optimization, Diffusion based algorithms, Mathematical finance, AI applications in finance and insruance

Major research field

Nonconvex optimization, Stochastic optimization, Diffusion based algorithms, Physics-informed neural networks, Neural differential equations, AI appl

Desired field of research

Nonconvex optimization, Stochastic optimization, Diffusion based algorithms, Physics-informed neural networks, Neural differential equations, AI appl

Research Publications

· Langevin dynamics based algorithm e-THεO POULA for stochastic problems with discontinuous stochastic gradient, D-Y Lim, A Neufeld, S Sabanis, and Y Zhang, Mathematics of Operations Research
· Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks, D-Y Lim and S Sabanis
Journal of Machine Learning Reserach (JMLR), 2024 (presented at Interational Conference on Machine Learning ICML, 2024)
· Stable neural stochastic differential equations in analyzing irregular time series data, Y Oh, D-Y Lim, and S Kim, International Conference on Learning Representations (ICLR), Spotlight, 2024
· Nonasymptotic estimates for TUSLA algorithm for nonconvex learning with applications to neural networks, D-Y Lim, A Neufeld, S Sabanis, and Y Zhang, IMA Journal of Numerical Analysis, 2023
· Static replication of barrier-type options via integral equations, K-K Kim and D-Y Lim, Quantitative Finance, 2021