no code implementations • 4 Mar 2024 • Rocco Caprio, Juan Kuntz, Samuel Power, Adam M. Johansen
We prove non-asymptotic error bounds for particle gradient descent (PGD)~(Kuntz et al., 2023), a recently introduced algorithm for maximum likelihood estimation of large latent variable models obtained by discretizing a gradient flow of the free energy.
no code implementations • 12 Dec 2023 • Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen
Maximum likelihood estimation (MLE) of latent variable models is often recast as an optimization problem over the extended space of parameters and probability distributions.
1 code implementation • 27 Apr 2022 • Juan Kuntz, Jen Ning Lim, Adam M. Johansen
(Neal and Hinton, 1998) recast maximum likelihood estimation of any given latent variable model as the minimization of a free energy functional $F$, and the EM algorithm as coordinate descent applied to $F$.
