A learning approach trains neural networks to approximate solutions of multiparametric GNEPs using NI gap loss with value surrogates, achieving large speedups and providing new existence conditions for continuous selections.
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math.OC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A simple variant of the Goldfarb-Idnani algorithm maintains several original properties for strongly monotone games despite a possibly non-symmetric pseudogradient matrix, though convergence to equilibrium is not guaranteed.
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Learning Approximate Solutions to Multiparametric Generalized Nash Equilibrium Problems
A learning approach trains neural networks to approximate solutions of multiparametric GNEPs using NI gap loss with value surrogates, achieving large speedups and providing new existence conditions for continuous selections.
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Towards A Goldfarb-Idnani Variant for Strongly Monotone Linear-Quadratic Games
A simple variant of the Goldfarb-Idnani algorithm maintains several original properties for strongly monotone games despite a possibly non-symmetric pseudogradient matrix, though convergence to equilibrium is not guaranteed.