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Optimization seeks extremal points in a function. When there are superextensively many optima, optimization algorithms are liable to get stuck. Under these conditions, generic algorithms tend to find marginal optima, which have many nearly…

Disordered Systems and Neural Networks · Physics 2024-07-25 Jaron Kent-Dobias

The mixed spherical models were recently found to violate long-held assumptions about mean-field glassy dynamics. In particular, the threshold energy, where most stationary points are marginal and that in the simpler pure models attracts…

Disordered Systems and Neural Networks · Physics 2024-01-03 Jaron Kent-Dobias

A method for the construction of approximate analytical expressions for the stationary marginal densities of general stochastic search processes is proposed. By the marginal densities, regions of the search space that with high probability…

Artificial Intelligence · Computer Science 2008-01-30 Arturo Berrones

We consider $h$-stable local optima of Ising spin glass models, defined as spin configurations such that for nearly all of the spins, flipping their values results in increasing energy by at least a given amount $h$. Spins satisfying this…

Probability · Mathematics 2025-09-10 Yatin Dandi , David Gamarnik , Lenka Zdeborová

The problem of binary minimization of a quadratic functional in the configuration space is discussed. In order to increase the efficiency of the random-search algorithm it is proposed to change the energy functional by raising to a power…

Disordered Systems and Neural Networks · Physics 2011-09-02 Iakov Karandashev , Boris Kryzhanovsky

Our goal is to discuss in detail the calculation of the mean number of stationary points and minima for random isotropic Gaussian fields on a sphere as well as for stationary Gaussian random fields in a background parabolic confinement.…

Mathematical Physics · Physics 2015-11-24 Yan V Fyodorov

Spin glass theory studies the structure of sublevel sets and minima (or near-minima) of certain classes of random functions in high dimension. Near-minima of random functions also play an important role in high-dimensional statistics and…

Probability · Mathematics 2026-02-27 Andrea Montanari

This paper develops approximate message passing algorithms to optimize multi-species spherical spin glasses. We first show how to efficiently achieve the algorithmic threshold energy identified in our companion work, thus confirming that…

Probability · Mathematics 2024-01-30 Brice Huang , Mark Sellke

We analyze the landscape of general smooth Gaussian functions on the sphere in dimension $N$, when $N$ is large. We give an explicit formula for the asymptotic complexity of the mean number of critical points of finite and diverging index…

Probability · Mathematics 2013-12-17 Antonio Auffinger , Gerard Ben Arous

Many important challenges in science and technology can be cast as optimization problems. When viewed in a statistical physics framework, these can be tackled by simulated annealing, where a gradual cooling procedure helps search for…

Disordered Systems and Neural Networks · Physics 2024-01-17 Mohamed Hibat-Allah , Estelle M. Inack , Roeland Wiersema , Roger G. Melko , Juan Carrasquilla

The statistical properties of the local optima (metastable states) of the infinite range Ising spin glass with p-spin interactions in the presence of an external magnetic field h are investigated analytically. The average number of optima…

Condensed Matter · Physics 2009-10-30 Viviane M de Oliveira , J F Fontanari

This paper treats the problem of minimizing a general continuously differentiable function subject to sparsity constraints. We present and analyze several different optimality criteria which are based on the notions of stationarity and…

Information Theory · Computer Science 2012-03-22 Amir Beck , Yonina C. Eldar

It is a folklore belief in the theory of spin glasses and disordered systems that out-of-equilibrium dynamics fail to find stable local optima exhibiting e.g. local strict convexity on physical time-scales. In the context of the…

Disordered Systems and Neural Networks · Physics 2026-04-02 Brice Huang , Mark Sellke

Marginal stability is the notion that stability is achieved, but only barely so. This property constrains the ensemble of configurations explored at low temperature in a variety of systems, including spin, electron and structural glasses. A…

Statistical Mechanics · Physics 2016-04-12 Le Yan , Marco Baity-Jesi , M. Mueller , Matthieu Wyart

We propose a framework for computing, optimizing and integrating with respect to a smooth marginal likelihood in statistical models that involve high-dimensional parameters/latent variables and continuous low-dimensional hyperparameters.…

Methodology · Statistics 2026-02-10 Omiros Papaspiliopoulos , Timothée Stumpf-Fétizon , Jonathan Weare

The idea of partial smoothness in optimization blends certain smooth and nonsmooth properties of feasible regions and objective functions. As a consequence, the standard first-order conditions guarantee that diverse iterative algorithms…

Optimization and Control · Mathematics 2018-07-10 Adrian S. Lewis , Jingwei Liang

We determine limiting equations for large asymmetric `spin glass' networks. The initial conditions are not assumed to be independent of the disordered connectivity: one of the main motivations for this is that allows one to understand how…

Disordered Systems and Neural Networks · Physics 2024-02-13 James MacLaurin , Moshe Silverstein , Pedro Vilanova

We derive a necessary condition for the existence of marginally stable circular orbits of test particles in stationary axisymmetric spacetimes which possess a refection symmetry with respect to the equatorial plane; photon orbits are also…

General Relativity and Quantum Cosmology · Physics 2016-08-08 Shabnam Beheshti , Edgar Gasperin

The scaling of fluctuations in the distribution of ground-state energies or costs with the system size N for Ising spin glasses is considered using an extensive set of simulations with the Extremal Optimization heuristic across a range of…

Disordered Systems and Neural Networks · Physics 2022-05-20 Stefan Boettcher

When searching for global optima of nonconvex unconstrained optimization problems, it is desirable that every local minimum be a global minimum. This property of having no spurious local minima is true in various problems of interest…

Optimization and Control · Mathematics 2023-11-16 Cédric Josz , Xiaopeng Li
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