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Related papers: On The Simulated Annealing In $\mathbf{R}^d$

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We use a localization procedure to weaken the growth assumptions of Royer [8], Miclo [4] and Zitt [9] concerning the continuous-time simulated annealing in $\mathbf{R}^d$. We show that a transition occurs for potentials growing like $a \log…

Probability · Mathematics 2020-09-18 Nicolas Fournier , Pierre Monmarché , Camille Tardif

We consider a continuous analogue of the simulated annealing algorithm in $R^d$. We prove a convergence result, under hypotheses weaker than the usual ones. In particular, we cover cases where the gradient of the potential goes to zero at…

Probability · Mathematics 2010-02-01 Pierre-André Zitt

We prove weak ergodicity of the inhomogeneous Markov process generated by the generalized transition probability of Tsallis and Stariolo under power-law decay of the temperature. We thus have a mathematical foundation to conjecture…

Statistical Mechanics · Physics 2009-10-31 Hidetoshi Nishimori , Jun-ichi Inoue

Many practical samplers rely on time-dependent drifts -- often induced by annealing or tempering schedules -- to improve exploration and stability. This motivates a unified non-asymptotic analysis of the corresponding Langevin diffusions…

Numerical Analysis · Mathematics 2026-05-12 Andreas Habring , Martin Zach

We provide a set of conditions which ensure the almost sure convergence of a class of simulated annealing algorithms on a bounded set $\mathcal{X}\subset\mathbb{R}^d$ based on a time-varying Markov kernel. The class of algorithms considered…

Probability · Mathematics 2017-07-07 Mathieu Gerber , Luke Bornn

Diffusion processes are fundamental in modelling stochastic dynamics in natural sciences. Recently, simulating such processes on complicated geometries has found applications for example in biology, where toroidal data arises naturally when…

Probability · Mathematics 2019-06-25 Mathias Højgaard Jensen , Anton Mallasto , Stefan Sommer

Diffusion models, which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a…

Machine Learning · Computer Science 2024-08-06 Gen Li , Yuting Wei , Yuejie Chi , Yuxin Chen

Simulated annealing is an effective and general means of optimization. It is in fact inspired by metallurgy, where the temperature of a material determines its behavior in thermodynamics. Likewise, in simulated annealing, the actions that…

Machine Learning · Computer Science 2020-07-01 Avrim Blum , Chen Dan , Saeed Seddighin

We study the convergence rate of continuous-time simulated annealing $(X_t; \, t \ge 0)$ and its discretization $(x_k; \, k =0,1, \ldots)$ for approximating the global optimum of a given function $f$. We prove that the tail probability…

Probability · Mathematics 2021-02-10 Wenpin Tang , Xun Yu Zhou

We provide a class of diffusion processes for continuous time-varying multivariate angular data with explicit transition probability densities, enabling exact likelihood inference. The presented diffusions are time-reversible and can be…

Methodology · Statistics 2024-09-05 Eduardo García-Portugués , Michael Sørensen

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a…

Machine Learning · Statistics 2007-09-20 A. Lecchini-Visintini , J. Lygeros , J. Maciejowski

A generic algorithm for the extraction of probabilistic (Bayesian) information about model parameters from data is presented. The algorithm propagates an ensemble of particles in the product space of model parameters and outputs. Each…

Computation · Statistics 2015-09-18 Carlo Albert

Annealing is the process of gradually lowering the temperature of a system to guide it towards its lowest energy states. In an accompanying paper [Luo et al. Phys. Rev. E 108, L052105 (2023)], we derived a general bound on annealing…

Statistical Mechanics · Physics 2023-11-20 Yutong Luo , Yi-Zheng Zhen , Xiangjing Liu , Daniel Ebler , Oscar Dahlsten

Density expansions for hypoelliptic diffusions $(X^1,...,X^d)$ are revisited. In particular, we are interested in density expansions of the projection $(X_T^1,...,X_T^l)$, at time $T>0$, with $l \leq d$. Global conditions are found which…

Probability · Mathematics 2013-05-30 J. D. Deuschel , P. K. Friz , A. Jacquier , S. Violante

In this paper we study the large time asymptotics of the flow of a dynamical system $X'=b(X)$ posed in the $d$-dimensional torus. Rather than using the classical unique ergodicity condition which is not fulfilled if $b$ vanishes at…

Dynamical Systems · Mathematics 2019-12-20 Marc Briane , Loïc Hervé

Simulated annealing solves global optimization problems by means of a random walk in a cooling energy landscape based on the objective function and a temperature parameter. However, if the temperature is decreased too quickly, this…

Optimization and Control · Mathematics 2025-04-14 Vincent Molin , Axel Ringh , Moritz Schauer , Akash Sharma

Score-based diffusion models, while achieving minimax optimality for sampling, are often hampered by slow sampling speeds due to the high computational burden of score function evaluations. Despite the recent remarkable empirical advances…

Machine Learning · Computer Science 2025-02-27 Gen Li , Changxiao Cai

The aim of this paper is to use the methods and results of symplectic homogenization (see [V4]) to prove existence of periodic orbits and invariant measures with rotation number depending on the differential of the Homogenized Hamiltonian.…

Dynamical Systems · Mathematics 2025-12-23 Claude Viterbo

We study the inhomogeneous Landau equation with Coulomb potential and derive a new continuation criterion: a smooth solution can be uniquely continued for as long as it remains bounded. This provides, to our knowledge, the first…

Analysis of PDEs · Mathematics 2026-05-22 William Golding , Christopher Henderson

Through a discussion of some typical unsteady hydrodynamic flows, we argue that the time averaged hydrodynamic functions at each point give a rather sparse filling of the local jet space. This situation then suggests a set of time dependent…

Fluid Dynamics · Physics 2014-07-08 Clifford Chafin
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