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Convex Analysis of the Mean Field Langevin Dynamics
[article]
2022
As an example of the nonlinear Fokker-Planck equation, the mean field Langevin dynamics attracts attention due to its connection to (noisy) gradient descent on infinitely wide neural networks in the mean field regime, and hence the convergence property of the dynamics is of great theoretical interest. In this work, we give a simple and self-contained convergence rate analysis of the mean field Langevin dynamics with respect to the (regularized) objective function in both continuous and discrete
doi:10.48550/arxiv.2201.10469
fatcat:myhxm6le7zfq5pl4dqcu4egsgy