The paper adapts forward and reverse gradient techniques from hyperparameter optimization to solve continuous high-dimensional Stackelberg games, with complexity trade-offs and an adversarial regression application.
On-line learning in neural networks 17(9), 142 (1998)
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Gradient Methods for Solving Stackelberg Games
The paper adapts forward and reverse gradient techniques from hyperparameter optimization to solve continuous high-dimensional Stackelberg games, with complexity trade-offs and an adversarial regression application.