Jan 22, 2019 · In this study, we analyze the non-asymptotic behavior of FLMC for non-convex optimization and prove finite-time bounds for its expected suboptimality.
Recent studies on diffusion-based sampling meth- ods have shown that Langevin Monte Carlo. (LMC) algorithms can be beneficial for non- convex optimization ...
Non-Asymptotic Analysis of FLMC for Non-Convex Optimization. Page 2. Introduction. Non-convex optimization problem: min f (x). Thanh Huy Nguyen,. Umut Simsekli ...
In this section, we precise the statement of Lemma 2 and provide the proof. Lemma S1. Let V and W be two random variables on Rd which have µ and ν as the ...
Jan 22, 2019 · In this study, we analyze the non-asymptotic behavior of FLA for non-convex optimization. ... optimization: Langevin Monte. Carlo and ...
In this study, we analyze the non-asymptotic behavior of FLMC for non-convex optimization and prove finite-time bounds for its expected suboptimality. Our ...
The ICML Logo above may be used on presentations. Right-click and choose download. It is a vector graphic and may be used at any scale. Useful links ...
Lower bounds are well-known for convex optimization and have helped guide the design of accelerated algorithms such as Nesterov's Accelerated Gradient Descent.
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Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization · Stochastic Fractional Hamiltonian Monte Carlo · Lévy Langevin Monte Carlo.
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Sep 4, 2024 · We study the Langevin-type algorithms for Gibbs distributions such that the potentials are dissipative and their weak gradients have the ...
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