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DR-submodular continuous functions are important objectives with wide real-world applications spanning MAP inference in determinantal point processes (DPPs), and mean-field inference for probabilistic submodular models, amongst others.…

Machine Learning · Computer Science 2019-05-27 An Bian , Kfir Y. Levy , Andreas Krause , Joachim M. Buhmann

The values of the determinant of Vandermonde matrices with real elements are analyzed both visually and analytically over the unit sphere in various dimensions. For three dimensions some generalized Vandermonde matrices are analyzed…

Classical Analysis and ODEs · Mathematics 2013-12-24 Karl Lundengård , Jonas Österberg , Sergei Silvestrov

Matrix--vector algorithms, particularly Krylov subspace methods, are widely viewed as the most effective algorithms for solving large systems of linear equations. This paper establishes lower bounds on the worst-case number of…

Data Structures and Algorithms · Computer Science 2026-02-19 Michał Dereziński , Ethan N. Epperly , Raphael A. Meyer

In this paper we formulate the problem of packing unequal rectangles/squares into a fixed size circular container as a mixed-integer nonlinear program. Here we pack rectangles so as to maximise some objective (e.g. maximise the number of…

Optimization and Control · Mathematics 2018-02-22 C. O. López , J. E. Beasley

In this paper, we present a significant improvement of Quick Hypervolume algorithm, one of the state-of-the-art algorithms for calculating exact hypervolume of the space dominated by a set of d-dimensional points. This value is often used…

Neural and Evolutionary Computing · Computer Science 2017-08-14 Andrzej Jaszkiewicz

In this paper, we present some explicit exponents in the estimates for the volumes of sub-level sets of polynomials on bounded sets, and applications to the decay of oscillatory integrals and the convergent of singular integrals.

Classical Analysis and ODEs · Mathematics 2021-11-30 Ta Lê Loi , Minh Quy Pham

The goal of this paper is to generalize the theory of triangularizing matrices to linear transformations of an arbitrary vector space, without placing any restrictions on the dimension of the space or on the base field. We define a…

Rings and Algebras · Mathematics 2018-03-21 Zachary Mesyan

The maximum volume principle is investigated as a means to solve the following problem: Given a set of arbitrary interpolation nodes, how to choose a set of polynomial basis functions for which the Lagrange interpolation problem is…

Numerical Analysis · Mathematics 2017-05-16 Vesa Kaarnioja

We relate Nekrasov partition functions, with arbitrary values of $\epsilon_1,\epsilon_2$ parameters, to matrix models for $\beta$-ensembles. We find matrix models encoding the instanton part of Nekrasov partition functions, whose measure,…

High Energy Physics - Theory · Physics 2010-04-30 Piotr Sułkowski

In this paper we derive the optimal linear shrinkage estimator for the high-dimensional mean vector using random matrix theory. The results are obtained under the assumption that both the dimension $p$ and the sample size $n$ tend to…

Statistics Theory · Mathematics 2018-07-17 Taras Bodnar , Ostap Okhrin , Nestor Parolya

The study of the additive volume of sets can be reduced to the case of one-dimensional sets. The exact values of the volume of extremal sets are given as a conjecture.

Number Theory · Mathematics 2014-12-17 Gregory A. Freiman

The low-rank matrix approximation problem is ubiquitous in computational mathematics. Traditionally, this problem is solved in spectral or Frobenius norms, where the accuracy of the approximation is related to the rate of decrease of the…

Numerical Analysis · Mathematics 2022-01-31 Stanislav Morozov , Nikolai Zamarashkin , Eugene Tyrtyshnikov

Recommender systems are essential tools in the digital landscape for connecting users with content that more closely aligns with their preferences. Matrix completion is a widely used statistical framework for such systems, aiming to predict…

Machine Learning · Statistics 2025-07-30 Aurore Archimbaud , Andreas Alfons , Ines Wilms

Random matrix models based on an integral over supermatrices are proposed as a natural extension of bosonic matrix models. The subtle nature of superspace integration allows these models to have very different properties from the analogous…

High Energy Physics - Theory · Physics 2015-06-26 Scott A. Yost

In this paper, maximum principles for Euclidean and hyperbolic discrete conformal structures on polyhedral surfaces are established. These maximum principles unify and generalize the maximum principles for vertex scalings and different…

Metric Geometry · Mathematics 2025-06-19 Yanwen Luo , Xu Xu , Chao Zheng

The problem of approximating a matrix by a low-rank one has been extensively studied. This problem assumes, however, that the whole matrix has a low-rank structure. This assumption is often false for real-world matrices. We consider the…

Data Structures and Algorithms · Computer Science 2025-11-05 Martino Ciaperoni , Aristides Gionis , Heikki Mannila

We characterize asymptotic collective behaviour of rectangular random matrices, the sizes of which tend to infinity at different rates: when embedded in a space of larger square matrices, independent rectangular random matrices are…

Operator Algebras · Mathematics 2008-03-04 Florent Benaych-Georges

The complete tree-level S-matrix of four dimensional ${\cal N}=4$ super Yang-Mills and ${\cal N} = 8$ supergravity has compact forms as integrals over the moduli space of certain rational maps. In this note we derive formulas for amplitudes…

High Energy Physics - Theory · Physics 2015-06-16 Freddy Cachazo , Song He , Ellis Ye Yuan

We describe algorithms for computing maximal determinants of binary circulant matrices of small orders. Here "binary matrix" means a matrix whose elements are drawn from $\{0,1\}$ or $\{-1,1\}$. We describe efficient parallel algorithms for…

Combinatorics · Mathematics 2021-02-23 Richard P. Brent , Adam B. Yedidia

The finite volume Laplacian can be defined in all dimensions and is a natural way to approximate the operator on a simplicial mesh. In the most general setting, its definition with orthogonal duals may require that not all volumes are…

Differential Geometry · Mathematics 2021-08-18 Thomas Doehrman , David Glickenstein