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Positive definite matrices abound in a dazzling variety of applications. This ubiquity can be in part attributed to their rich geometric structure: positive definite matrices form a self-dual convex cone whose strict interior is a…

Functional Analysis · Mathematics 2013-12-31 Suvrit Sra

In this article we study commutant lifting, more generally intertwining lifting, for different reproducing kernel Hilbert spaces over two domains in $\mathbb{C}^n$, namely the unit ball and the unit polydisc. The reproducing kernel Hilbert…

Functional Analysis · Mathematics 2020-04-07 Sibaprasad Barik , Monojit Bhattacharjee , B. Krishna Das

This paper proves a corner occupying theorem for the two-dimensional integral rectangle packing problem, stating that if it is possible to orthogonally place n arbitrarily given integral rectangles into an integral rectangular container…

Discrete Mathematics · Computer Science 2011-11-17 Wenqi Huang , Tao Ye , Duanbing Chen

In this paper we show how specific families of positive definite kernels serve as powerful tools in analyses of iteration algorithms for multiple layer feedforward Neural Network models. Our focus is on particular kernels that adapt well to…

Machine Learning · Computer Science 2023-01-09 Palle E. T. Jorgensen , Myung-Sin Song , James Tian

In this paper we study the kernelization of the $d$-Path Vertex Cover ($d$-PVC) problem. Given a graph $G$, the problem requires finding whether there exists a set of at most $k$ vertices whose removal from $G$ results in a graph that does…

Data Structures and Algorithms · Computer Science 2022-07-26 Radovan Červený , Pratibha Choudhary , Ondřej Suchý

The notion of Carry Value Transformation (CVT) is a model of Discrete Deterministic Dynamical System. In this paper, we have studied some interesting properties of CVT and proved that (1) the addition of any two non-negative integers is…

Discrete Mathematics · Computer Science 2011-10-04 Suryakanta Pal , Sudhakar Sahoo , Birendra Kumar Nayak

We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods. The proposed kernel is defined based on a hierarchical partitioning of the underlying data domain, where…

Machine Learning · Computer Science 2017-08-15 Jie Chen , Haim Avron , Vikas Sindhwani

A variant of the classical optimal transportation problem is: among all joint measures with fixed marginals and which are dominated by a given density, find the optimal one. Existence and uniqueness of solutions to this variant were…

Optimization and Control · Mathematics 2018-01-23 Jonathan Korman , Robert J. McCann

The transport properties of dense QCD matter play a crucial role in the physics of neutron stars and their mergers, but are notoriously difficult to study with traditional quantum field theory tools. Specializing to the case of unpaired…

High Energy Physics - Theory · Physics 2022-04-06 Carlos Hoyos , Niko Jokela , Matti Järvinen , Javier G. Subils , Javier Tarrio , Aleksi Vuorinen

We present an alternative way of solving the steerable kernel constraint that appears in the design of steerable equivariant convolutional neural networks. We find explicit real and complex bases which are ready to use, for different…

Machine Learning · Computer Science 2026-03-16 Alan Garbarz

Optimal transport is widely used in pure and applied mathematics to find probabilistic solutions to hard combinatorial matching problems. We extend the Wasserstein metric and other elements of optimal transport from the matching of sets to…

Optimization and Control · Mathematics 2019-07-16 Evan Patterson

The histogram is an analysis tool in widespread use within many sciences, with high energy physics as a prime example. However, there exists an inherent bias in the choice of binning for the histogram, with different choices potentially…

Data Analysis, Statistics and Probability · Physics 2014-05-21 Abram Krislock , Nathan Krislock

A generalization of the Wasserstein metric, the integrated transportation distance, establishes a novel distance between probability kernels of Markov systems. This metric serves as the foundation for an efficient approximation technique,…

Machine Learning · Computer Science 2023-12-07 Zhengqi Lin , Andrzej Ruszczynski

We provide convergent hierarchies for the cone C of copositive matrices and its dual, the cone of completely positive matrices. In both cases the corresponding hierarchy consists of nested spectrahedra and provide outer (resp. inner)…

Optimization and Control · Mathematics 2012-01-20 Jean Bernard Lasserre

The Riemannian metric on the manifold of positive definite matrices is defined by a kernel function $\phi$ in the form $K_D^\phi(H,K)=\sum_{i,j}\phi(\lambda_i,\lambda_j)^{-1} Tr P_iHP_jK$ when $\sum_i\lambda_iP_i$ is the spectral…

Mathematical Physics · Physics 2008-11-08 F. Hiai , D. Petz

Positivstellensatz is a fundamental result in real algebraic geometry providing algebraic certificates for positivity of polynomials on semialgebraic sets. In this article Positivstellens\"atze for trace polynomials positive on…

Rings and Algebras · Mathematics 2019-01-23 Igor Klep , Špela Špenko , Jurij Volčič

We compute the weighted enumeration of plane partitions contained in a given box with complementation symmetry where adding one half of an orbit of cubes and removing the other half of the orbit changes the weight by -1 as proposed by…

Combinatorics · Mathematics 2007-05-23 Theresia Eisenkölbl

An operator convex function on (0,\infty) which satisfies the symmetry condition k(1/x) = x k(x) can be used to define a type of non-commutative multiplication by a positive definite matrix (or its inverse) using the primitive concepts of…

Quantum Physics · Physics 2021-12-28 Fumio Hiai , Hideki Kosaki , Denes Petz , Mary Beth Ruskai

Real-world physical systems, like composite materials and porous media, exhibit complex heterogeneities and multiscale nature, posing significant computational challenges. Computational homogenization is useful for predicting macroscopic…

Computational Engineering, Finance, and Science · Computer Science 2024-07-29 Yuki Sato , Yuto Lewis Terashima , Ruho Kondo

We study analytic models of operators of class $C_{\cdot 0}$ with natural positivity assumptions. In particular, we prove that for an $m$-hypercontraction $T \in C_{\cdot 0}$ on a Hilbert space $\mathcal{H}$, there exists a Hilbert space…

Functional Analysis · Mathematics 2016-02-26 Monojit Bhattacharjee , Jaydeb Sarkar
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