Mirror Descent Algorithms for Minimizing Interacting Free Energy
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Abstract (arXiv)
This note considers the problem of minimizing interacting free energy. Motivated by the mirror descent algorithm, for a given interacting free energy, we propose a descent dynamics with a novel metric that takes into consideration the reference measure and the interacting term. This metric naturally suggests a monotone reparameterization of the probability measure. By discretizing the reparameterized descent dynamics with the explicit Euler method, we arrive at a new mirror-descent-type algorithm for minimizing interacting free energy. Numerical results are included to demonstrate the efficiency of the proposed algorithms.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Apr 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1.
3 papers.
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- 2022Convex Analysis of the Mean Field Langevin Dynamics25 Jan 2022
- 2021Approximate Newton policy gradient algorithms5 Oct 2021