21 citations · 30 across the 6 of their papers we have counts for
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math.NA2023
DynAMO: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws
Tarik Dzanic, Ketan Mittal, Dohyun Kim +4
We introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost a…
math.OC2023
An Adaptive Sampling Augmented Lagrangian Method for Stochastic Optimization with Deterministic Constraints
Raghu Bollapragada, Cem Karamanli, Brendan Keith +3
The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective funct…