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Related papers: Linear rank inequalities on five or more variables

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Rank invariants are a parametrized version of Betti numbers of a space multi-filtered by a continuous vector-valued function. In this note we give a sufficient condition for their finiteness. This condition is sharp for spaces embeddable in…

Algebraic Topology · Mathematics 2010-01-05 Francesca Cagliari , Claudia Landi

Equivalencies of many basic elementary inequalities are given

Classical Analysis and ODEs · Mathematics 2008-09-04 P. S. Bullen

Ranking algorithms are deployed widely to order a set of items in applications such as search engines, news feeds, and recommendation systems. Recent studies, however, have shown that, left unchecked, the output of ranking algorithms can…

Data Structures and Algorithms · Computer Science 2018-07-31 L. Elisa Celis , Damian Straszak , Nisheeth K. Vishnoi

Whereas Shannon entropy is related to the growth rate of multinomial coefficients, we show that the quadratic entropy (Tsallis 2-entropy) is connected to their $q$-deformation; when $q$ is a prime power, these $q$-multinomial coefficients…

Mathematical Physics · Physics 2020-03-27 Juan Pablo Vigneaux

The existence of an unbounded sequence of solutions to a conformally invariant elliptic equation having nonlocal critical-power nonlinearity is established. The primary obstacle to establishing existence of solutions is the failure of…

Analysis of PDEs · Mathematics 2025-09-16 Mona Almutairi , Mathew Gluck

We seek to impose linear, equality constraints in feedforward neural networks. As top layer predictors are usually nonlinear, this is a difficult task if we seek to deploy standard convex optimization methods and strong duality. To overcome…

Machine Learning · Computer Science 2023-01-10 Anand Rangarajan , Pan He , Jaemoon Lee , Tania Banerjee , Sanjay Ranka

Cheeger-type inequalities in which the decomposability of a graph and the spectral gap of its Laplacian mutually control each other play an important role in graph theory and network analysis, in particular in the context of expander…

Combinatorics · Mathematics 2026-02-06 Jürgen Jost , Dong Zhang

In this paper, we give a new inequality for convex functions of real variables, and we apply this inequality to obtain considerable generalizations, refinements, and reverses of the Young and Heinz inequalities for positive scalars.…

Functional Analysis · Mathematics 2017-03-23 Yousef Al-Manasrah , Fuad Kittaneh

Establishing the limiting distribution of Chatterjee's rank correlation for a general, possibly non-independent, pair of random variables has been eagerly awaited by many. This paper shows that (a) Chatterjee's rank correlation is…

Statistics Theory · Mathematics 2025-06-05 Zhexiao Lin , Fang Han

We show that an information-theoretic property of Shannon's entropy power, known as concavity of entropy power, can be fruitfully employed to prove inequalities in sharp form. In particular, the concavity of entropy power implies the…

Information Theory · Computer Science 2012-07-13 Giuseppe Toscani

We prove an infinite sequence of inequalities among scalar polynomial invariants of symmetric rank-2 tensors of Segre types $A1$, $A3$, and $B$. In particular, these inequalities apply to the Ricci tensor and the energy-momentum tensor. If…

General Relativity and Quantum Cosmology · Physics 2026-03-20 Sebastian J. Szybka , Yaroslava Kravetska , Kornelia Nikiel

Some inequalities for positive linear maps on matrix algebras are given, especially asymmetric extensions of Kadison's inequality and several operator versions of Chebyshev's inequality. We also discuss well-known results around the matrix…

Functional Analysis · Mathematics 2010-03-12 Jean-Christophe Bourin , Éric Ricard

We use representation theory to construct spaces of matrices of constant rank. These spaces are parametrized by the natural representation of the general linear group or the symplectic group. We present variants of this idea, with more…

Algebraic Geometry · Mathematics 2022-12-09 J. M. Landsberg , L. Manivel

After the phenomenal success of the PageRank algorithm, many researchers have extended the PageRank approach to ranking graphs with richer structures beside the simple linkage structure. In some scenarios we have to deal with…

Numerical Analysis · Mathematics 2018-11-15 Gianna M. Del Corso , Francesco Romani

In this paper we investigate connections between linear sets and subspaces of linear maps. We give a geometric interpretation of the results of [18, Section 5] on linear sets on a projective line. We extend this to linear sets in arbitrary…

Combinatorics · Mathematics 2018-06-18 John Sheekey , Geertrui Van de Voorde

In this paper we consider the variable inequality problem, that is, to find a solution of the inclusion given by the sum of a function and a point-to-cone application. This problem can be seen as a generalization of the classical system…

Optimization and Control · Mathematics 2014-09-10 J. Y. Bello Cruz , L. R. Lucambio Perez , G. Bouza Allende

The new estimates of the conditional Shannon entropy are introduced in the framework of the model describing a discrete response variable depending on a vector of d factors having a density w.r.t. the Lebesgue measure in R^d. Namely, the…

Statistics Theory · Mathematics 2018-04-25 Alexander Bulinski , Alexey Kozhevin

Let $n,p,r$ be positive integers with $n \geq p\geq r$. A rank-$\overline{r}$ subset of $n$ by $p$ matrices (with entries in a field) is a subset in which every matrix has rank less than or equal to $r$. A classical theorem of Flanders…

Rings and Algebras · Mathematics 2016-04-21 Clément de Seguins Pazzis

The 60 real vectors derived from the vertices of a 600-cell are shown to yield a number of pentagon inequalities that are satisfied by realistic noncontextual theories but violated by quantum mechanics. The replicas of these inequalities…

Quantum Physics · Physics 2011-11-22 Mordecai Waegell , P. K. Aravind

One of the goals of probabilistic inference is to decide whether an empirically observed distribution is compatible with a candidate Bayesian network. However, Bayesian networks with hidden variables give rise to highly non-trivial…

Machine Learning · Statistics 2014-10-14 R. Chaves , L. Luft , T. O. Maciel , D. Gross , D. Janzing , B. Schölkopf