3 papers
math.OC2026
Random Gradient-Free Optimization in Infinite Dimensional Spaces
Caio Peixoto, Daniel Csillag, Bernardo F. P. da Costa +1
We propose a new gradient-free method for infinite-dimensional optimization in Hilbert spaces that requires only the computation of directional derivatives. Though functional optim…
cs.LG2026
Deep Learning and Elicitability for McKean-Vlasov FBSDEs With Common Noise
Felipe J. P. Antunes, Yuri F. Saporito, Sebastian Jaimungal
We present a novel numerical method for solving McKean--Vlasov forward--backward stochastic differential equations (MV--FBSDEs) with common noise, combining Picard iterations, elic…
q-fin.TR2026
Optimal Trading in Automated Market Makers with Deep Learning
Sebastian Jaimungal, Yuri F. Saporito, Max O. Souza +1
This article explores the optimisation of trading strategies in Constant Function Market Makers (CFMMs) and centralised exchanges. We develop a model that accounts for the interact…