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Found 5 papers, 1 papers with code
SDEs for Minimax Optimization
Minimax optimization problems have attracted a lot of attention over the past few years, with applications ranging from economics to machine learning.
An SDE for Modeling SAM: Theory and Insights
We study the SAM (Sharpness-Aware Minimization) optimizer which has recently attracted a lot of interest due to its increased performance over more classical variants of stochastic gradient descent.
Risk Sharing with Deep Neural Networks
We consider the problem of optimally sharing a financial position among agents with potentially different reference risk measures.
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics
Many finance, physics, and engineering phenomena are modeled by continuous-time dynamical systems driven by highly irregular (stochastic) inputs.
Empirics on the expressiveness of Randomized Signature
Time series analysis is a widespread task in Natural Sciences, Social Sciences and Engineering.
