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We consider convex-concave saddle point problems with a separable structure and non-strongly convex functions. We propose an efficient stochastic block coordinate descent method using adaptive primal-dual updates, which enables flexible…

Machine Learning · Statistics 2015-11-24 Zhanxing Zhu , Amos J. Storkey

We present a new solution of the asymmetric two-matrix model in the large $N$ limit which only involves a saddle point analysis. The model can be interpreted as Ising in the presence of a magnetic field, on random dynamical lattices with…

Statistical Mechanics · Physics 2007-05-23 P. Zinn-Justin

The Alternating Direction Method of Multipliers (ADMM) has gained significant attention across a broad spectrum of machine learning applications. Incorporating the over-relaxation technique shows potential for enhancing the convergence rate…

Optimization and Control · Mathematics 2024-01-02 Jintao Song , Wenqi Lu , Yunwen Lei , Yuchao Tang , Zhenkuan Pan , Jinming Duan

This paper aims to answer an open question recently posed in the literature, that is to find a fast exact method for solving the p-dispersion-sum problem (PDSP), a nonconcave quadratic binary maximization problem. We show that, since the…

Optimization and Control · Mathematics 2022-07-25 Sandy Spiers , Hoa T. Bui , Ryan Loxton

Gaussian process regression (GPR) is a powerful machine learning method which has recently enjoyed wider use, in particular in physical sciences. In its original formulation, GPR uses a square matrix of covariances among training data and…

Numerical Analysis · Mathematics 2023-09-08 Sergei Manzhos , Manabu Ihara

The paper presents a new stiffness modeling method for overconstrained parallel manipulators with flexible links and compliant actuating joints. It is based on a multidimensional lumped-parameter model that replaces the link flexibility by…

Robotics · Computer Science 2009-04-02 Anatoly Pashkevich , Damien Chablat , Philippe Wenger

A binary liquid near its consolute point exhibits critical fluctuations of the local composition; the diverging correlation length has always challenged simulations. The method of choice for the calculation of critical points in the phase…

Statistical Mechanics · Physics 2021-04-29 Yogyata Pathania , Dipanjan Chakraborty , Felix Höfling

We consider Robin Laplace operators on a class of two-dimensional domains with cusps. Our main results include the formula for the asymptotic distribution of the eigenvalues of such operators. In particular, we show how the eigenvalue…

Spectral Theory · Mathematics 2014-02-26 Hynek Kovarik

This paper proposes a GPU-accelerated optimization framework for collision avoidance problems where the controlled objects and the obstacles can be modeled as the finite union of convex polyhedra. A novel collision avoidance constraint is…

Robotics · Computer Science 2024-06-12 Zeming Wu , Zhuping Wang , Hao Zhang

The two-particle models in de Sitter space-time with time-asymmetric retarded-advanced interactions are constructed. Particular cases of the field-type electromagnetic and scalar interactions are considered. The manifestly covariant…

General Relativity and Quantum Cosmology · Physics 2026-02-18 Askold Duviryak

Despite the performance advantages of modern sampling-based motion planners, solving high dimensional planning problems in near real-time remains a challenge. Applications include hyper-redundant manipulators, snake-like and humanoid…

Robotics · Computer Science 2018-02-02 Marios P. Xanthidis , Joel M. Esposito , Ioannis Rekleitis , Jason M. O'Kane

Multi-type Markov point processes offer a flexible framework for modelling complex multi-type point patterns where it is pertinent to capture both interactions between points as well as large scale trends depending on observed covariates.…

Methodology · Statistics 2025-10-15 Ib Thorsgaard Jensen , Jean-François Coeurjolly , Rasmus Waagepetersen

The exceptional region of the parameter space (ERPS) of the two Higgs doublet model (2HDM) is defined to be the parameter regime where the scalar potential takes on a very special form. In the standard parameterization of the 2HDM scalar…

High Energy Physics - Phenomenology · Physics 2022-06-30 Howard E. Haber , Joao P. Silva

A wide range of equations related to free surface motion in two dimensions exhibit the formation of cusp singularities either in time, or as function of a parameter. We review a number of specific examples, relating in particular to fluid…

Mathematical Physics · Physics 2009-10-20 J. Eggers M. A. Fontelos

We consider a parametric convex quadratic programming, CQP, relaxation for the quadratic knapsack problem, QKP. This relaxation maintains partial quadratic information from the original QKP by perturbing the objective function to obtain a…

Optimization and Control · Mathematics 2019-06-11 Marcia Fampa , Daniela Cristina Lubke , Fei Wang , Henry Wolkowicz

In conformal field theory, momentum eigenstates can be parameterized by a pair of real spinors, in terms of which special conformal transformations take a simpler form. This well-known fact allows to express 2-point functions of primary…

High Energy Physics - Theory · Physics 2022-03-30 Marc Gillioz

This paper is devoted to the study of $L^p$-maximal regularity for non-autonomous linear evolution equations of the form \begin{equation*}\label{Multi-pert1-diss-non} \dot u(t)+A(t)B(t)u(t)=f(t)\ \ t\in[0,T],\ \ u(0)=u_0. \end{equation*}…

Functional Analysis · Mathematics 2016-04-26 Björn Augner , Birgit Jacob , Hafida Laasri

The half-filled two-dimensional Hubbard model in presence of a uniform and static parallel magnetic field has been studied by means of the Composite Operator Method. A fully self-consistent solution, fulfilling all the constrains coming…

Strongly Correlated Electrons · Physics 2007-05-23 A. Avella , F. Mancini

We consider generic families $X_\param$ of smooth dynamical systems depending on parameters $\param\in P$ where $P$ is a 2-dimensional simply connected domain and assume that each $X_\param$ only has a finite number of restpoints and…

Dynamical Systems · Mathematics 2025-02-06 David A Rand , Meritxell Saez

Gaussian Processes are used in many applications to model spatial phenomena. Within this context, a key issue is to decide the set of locations where to take measurements so as to obtain a better approximation of the underlying function.…

Emerging Technologies · Computer Science 2019-01-31 Lorenzo Bottarelli , Alessandro Farinelli