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Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime.

, and . CoRR, (2020)

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Temporal-difference learning for nonlinear value function approximation in the lazy training regime., and . CoRR, (2019)Urgency-aware optimal routing in repeated games through artificial currencies., , , and . Eur. J. Control, (2021)Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes., and . MSML, volume 145 of Proceedings of Machine Learning Research, page 37-74. PMLR, (2021)Urgency-aware Optimal Routing in Repeated Games through Artificial Currencies., , , and . CoRR, (2020)Global optimality of Elman-type RNNs in the mean-field regime., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 196-227. PMLR, (2023)Fair Artificial Currency Incentives in Repeated Weighted Congestion Games: Equity vs. Equality., , , and . CoRR, (2024)Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime., and . CoRR, (2020)A Homotopic Approach to Policy Gradients for Linear Quadratic Regulators with Nonlinear Controls., and . CDC, page 1588-1595. IEEE, (2022)Global Optimality of Elman-type RNN in the Mean-Field Regime., , and . CoRR, (2023)Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime., and . ICLR, OpenReview.net, (2021)