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Large-scale saddle-point problems arise in such machine learning tasks as GANs and linear models with affine constraints. In this paper, we study distributed saddle-point problems (SPP) with strongly-convex-strongly-concave smooth…

Optimization and Control · Mathematics 2022-10-04 Dmitriy Metelev , Alexander Rogozin , Alexander Gasnikov , Dmitry Kovalev

A method for locating first order saddle points on the energy surface of a magnetic system is described and several applications presented where the mechanism of various magnetic transitions is identified. The starting point for the…

Computational Physics · Physics 2025-01-17 Hendrik Schrautzer , Moritz Sallermann , Pavel F. Bessarab , Hannes Jónsson

For a real valued function, a point is critical if its derivatives are zero, and a critical point is a saddle point if it is not a local extrema. In this paper, we study algorithms to find saddle points of general Morse index. Our approach…

Numerical Analysis · Mathematics 2010-06-22 C. H. Jeffrey Pang

We prove that for a wide class of quantum spin systems with isotropic Heisenberg coupling the energy eigenvalues which belong to a total spin quantum number S have upper and lower bounds depending at most quadratically on S. The only…

Statistical Mechanics · Physics 2009-11-07 H. -J. Schmidt , J. Schnack , Marshall Luban

Non-convex optimal control arises from various applications but may contain multiple stationary points. Classical solvers usually perform a ``local'' search near a saddle point or a local minimum, thus rely on good initial guess to reach…

Optimization and Control · Mathematics 2025-12-02 Ning Du , Yanlin Liu , Lei Zhang , Xiangcheng Zheng

The complexity and unpredictability of postbuckling responses in even simple thin shells have raised great challenges to emerging technologies exploiting buckling transitions. Here we comprehensively survey the buckling landscapes to show…

Materials Science · Physics 2019-10-22 Jack Panter , Junbo Chen , Teng Zhang , Halim Kusumaatmaja

We introduce a tensor network algorithm for the solution of $p$-spin models. We show that bond compression through rank-revealing decompositions performed during the tensor network contraction resolves logical redundancies in the system…

Statistical Mechanics · Physics 2024-10-30 Benjamin Lanthier , Jeremy Côté , Stefanos Kourtis

We consider strongly-convex-strongly-concave saddle-point problems with general non-bilinear objective and different condition numbers with respect to the primal and the dual variables. First, we consider such problems with smooth composite…

Optimization and Control · Mathematics 2021-06-15 Vladislav Tominin , Yaroslav Tominin , Ekaterina Borodich , Dmitry Kovalev , Alexander Gasnikov , Pavel Dvurechensky

This paper studies the saddle point problem of polynomials. We give an algorithm for computing saddle points. It is based on solving Lasserre's hierarchy of semidefinite relaxations. Under some genericity assumptions on defining…

Optimization and Control · Mathematics 2021-06-10 Jiawang Nie , Zi Yang , Guangming Zhou

The energy landscapes of proteins have evolved to be different from most random heteropolymers. Many studies have concluded that evolutionary selection for rapid and reliable folding to a given structure that is stable at biological…

Disordered Systems and Neural Networks · Physics 2009-11-10 Steven S. Plotkin , Peter G. Wolynes

Automata networks are a versatile model of finite discrete dynamical systems composed of interacting entities (the automata), able to embed any directed graph as a dynamics on its space of configurations (the set of vertices, representing…

Discrete Mathematics · Computer Science 2025-09-24 Aliénor Goubault-Larrecq , Kévin Perrot

We analyze the behavior of randomized coordinate gradient descent for nonconvex optimization, proving that under standard assumptions, the iterates almost surely escape strict saddle points. By formulating the method as a nonlinear random…

Optimization and Control · Mathematics 2025-08-12 Ziang Chen , Yingzhou Li , Zihao Li

In this paper, we present novel randomized algorithms for solving saddle point problems whose dual feasible region is given by the direct product of many convex sets. Our algorithms can achieve an ${\cal O}(1/N)$ and ${\cal O}(1/N^2)$ rate…

Optimization and Control · Mathematics 2015-11-16 Cong Dang , Guanghui Lan

This paper depicts algorithms for solving the decision Boolean Satisfiability Problem. An extreme problem is formulated to analyze the complexity of algorithms and the complexity for solving it. A novel and easy reformulation as a lottery…

Computational Complexity · Computer Science 2016-04-15 Carlos Barrón-Romero

The article is devoted to the development of algorithmic methods ensuring efficient complexity bounds for strongly convex-concave saddle point problems in the case when one of the groups of variables is high-dimensional, and the other is…

Optimization and Control · Mathematics 2022-10-26 Egor Gladin , Ilya Kuruzov , Fedor Stonyakin , Dmitry Pasechnyuk , Mohammad Alkousa , Alexander Gasnikov

We explore recent progress and open questions concerning local minima and saddle points of the Cahn--Hilliard energy in $d\geq 2$ and the critical parameter regime of large system size and mean value close to $-1$. We employ the String…

Analysis of PDEs · Mathematics 2025-02-25 Tobias Grafke , Sebastian Scholtes , Alfred Wagner , Maria G. Westdickenberg

We study the limiting distribution of critical points and extrema of random spherical harmonics, in the high energy limit. In particular, we first derive the density functions of extrema and saddles; we then provide analytic expressions for…

Mathematical Physics · Physics 2018-01-09 Valentina Cammarota , Domenico Marinucci , Igor Wigman

Computing saddle points with a prescribed Morse index on potential energy surfaces is crucial for characterizing transition states for nosie-induced rare transition events in physics and chemistry. Many numerical algorithms for this type of…

Optimization and Control · Mathematics 2025-01-28 Shuting Gu , Hao Zhang , Xiaoqun Zhang , Xiang Zhou

A central challenge to using first-order methods for optimizing nonconvex problems is the presence of saddle points. First-order methods often get stuck at saddle points, greatly deteriorating their performance. Typically, to escape from…

Machine Learning · Computer Science 2017-09-06 Sashank J Reddi , Manzil Zaheer , Suvrit Sra , Barnabas Poczos , Francis Bach , Ruslan Salakhutdinov , Alexander J Smola

Large numbers of ground states of two-dimensional Ising spin glasses with periodic boundary conditions in both directions are calculated for sizes up to 40^2. A combination of a genetic algorithm and Cluster-Exact Approximation is used. For…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann
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