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Numerous interesting properties in nonlinear systems analysis can be written as polynomial optimization problems with nonconvex sum-of-squares problems. To solve those problems efficiently, we propose a sequential approach of local…

Optimization and Control · Mathematics 2023-10-03 Torbjørn Cunis , Benoît Legat

We present and study approximate notions of dimensional and margin complexity, which correspond to the minimal dimension or norm of an embedding required to approximate, rather then exactly represent, a given hypothesis class. We show that…

Machine Learning · Computer Science 2020-03-10 Pritish Kamath , Omar Montasser , Nathan Srebro

In scattered data approximation, the span of a finite number of translates of a chosen radial basis function is used as approximation space and the basis of translates is used for representing the approximate. However, this natural choice…

Numerical Analysis · Mathematics 2024-08-22 Helmut Harbrecht , Rüdiger Kempf , Michael Multerer

We study the Cowling approximation by analytical means as applied to a system of linear differential equations arising from models of non-radial stellar pulsation. We consider various asymptotic cases, including those of high harmonic…

Mathematical Physics · Physics 2025-07-22 Christopher J. Winfield

We study localization and delocalization in a class of non-hermitean Hamiltonians inspired by the problem of vortex pinning in superconductors. In various simplified models we are able to obtain analytic descriptions, in particular of the…

Disordered Systems and Neural Networks · Physics 2009-10-30 Joshua Feinberg , A. Zee

Given an intractable target density $p$, variational inference (VI) attempts to find the best approximation $q$ from a tractable family $Q$. This is typically done by minimizing the exclusive Kullback-Leibler divergence, $\text{KL}(q||p)$.…

Machine Learning · Statistics 2025-11-04 Charles C. Margossian , Lawrence K. Saul

Considering a "random walk in a random environment" in a topologically closed circuit, we explore the implications of the percolation and sliding transitions for its relaxation modes. A complementary question regarding the "delocalization"…

Statistical Mechanics · Physics 2016-03-11 Daniel Hurowitz , Doron Cohen

We consider monotonic, multiple regression for a set of contiguous regions (lattice data). The regression functions permissibly vary between regions and exhibit geographical structure. We develop new Bayesian non-parametric methodology…

Methodology · Statistics 2019-04-16 Christian Rohrbeck , Deborah Costain , Arnoldo Frigessi

We show how to use a variational approximation to the logistic function to perform approximate inference in Bayesian networks containing discrete nodes with continuous parents. Essentially, we convert the logistic function to a Gaussian,…

Artificial Intelligence · Computer Science 2013-01-30 Kevin Murphy

We study the complexity of approximations to the normalized information distance. We introduce a hierarchy of computable approximations by considering the number of oscillations. This is a function version of the difference hierarchy for…

Logic · Mathematics 2019-11-15 Klaus Ambos-Spies , Wolfgang Merkle , Sebastiaan A. Terwijn

The nonlinear space-fractional problems often allow multiple stationary solutions, which can be much more complicated than the corresponding integer-order problems. In this paper, we systematically compute the solution landscapes of…

Numerical Analysis · Mathematics 2022-08-31 Bing Yu , Lei Zhang , Pingwen Zhang , Xiangcheng Zheng

Numerical homogenization aims to efficiently and accurately approximate the solution space of an elliptic partial differential operator with arbitrarily rough coefficients in a $d$-dimensional domain. The application of the inverse operator…

Numerical Analysis · Mathematics 2022-11-24 Moritz Hauck , Daniel Peterseim

This paper discusses a methodology for determining a functional representation of a random process from a collection of scattered pointwise samples. The present work specifically focuses onto random quantities lying in a high dimensional…

Numerical Analysis · Mathematics 2014-01-03 Lionel Mathelin

In this paper, we study the existence of the random approximations and fixed points for random almost lower semicontinuous operators defined on finite dimensional Banach spaces, which in addition, are condensing or 1-set-contractive. Our…

Probability · Mathematics 2015-07-13 Monica Patriche

To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part. We propose a truncation-based approximation that employs a state-space lumping scheme, aggregating…

Machine Learning · Statistics 2021-05-05 Michael Backenköhler , Luca Bortolussi , Gerrit Großmann , Verena Wolf

In this paper, we present a method to solve the quantum marginal problem for symmetric $d$-level systems. The method is built upon an efficient semi-definite program that determines the compatibility conditions of an $m$-body reduced…

Quantum Physics · Physics 2021-05-26 Albert Aloy , Matteo Fadel , Jordi Tura

We present a stochastic and variational aspect of the Lax-Friedrichs scheme applied to hyperbolic scalar conservation laws. This is a finite difference version of Fleming's results ('69) that the vanishing viscosity method is characterized…

Numerical Analysis · Mathematics 2012-05-11 Kohei Soga

Domain specific localization of eigenstates has been a persistent observation for systems with local symmetries. The underlying mechanism for this localization behaviour has however remained elusive. We provide here an analysis of locally…

Quantum Physics · Physics 2024-01-19 Peter Schmelcher

Using Lie symmetry methods for differential equations we have investigated the symmetries of a Lagrangian for a plane symmetric static spacetime. Perturbing this Lagrangian we explore its approximate symmetries. It has a non-trivial…

General Relativity and Quantum Cosmology · Physics 2009-01-16 Ibrar Hussain , Asghar Qadir

In this paper, we address a way to reduce the total computational cost of meshless approximation by reducing the required stencil size through spatial variation of computational node regularity. Rather than covering the entire domain with…

Numerical Analysis · Mathematics 2024-04-04 Mitja Jančič , Miha Rot , Gregor Kosec