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We study the top-$K$ ranking problem where the goal is to recover the set of top-$K$ ranked items out of a large collection of items based on partially revealed preferences. We consider an adversarial crowdsourced setting where there are…

Information Retrieval · Computer Science 2016-02-16 Changho Suh , Vincent Y. F. Tan , Renbo Zhao

In this paper, we study the symmetric rank of products of linear forms and an irreducible quadratic form. The main result presents a new, non-trivial lower bound for the rank, and the arguments rely on the apolarity lemma. In the special…

Algebraic Geometry · Mathematics 2026-01-07 Liena Colarte-Gómez , Francesco Galuppi

We study the tensor rank of the tensor corresponding to the algebra of n-variate complex polynomials modulo the dth power of each variable. As a result we find a sequence of tensors with a large gap between rank and border rank, and thus a…

Commutative Algebra · Mathematics 2017-03-24 Jeroen Zuiddam

We investigate the rank of random (symmetric) sparse matrices. Our main finding is that with high probability, any dependency that occurs in such a matrix is formed by a set of few rows that contains an overwhelming number of zeros. This…

Probability · Mathematics 2007-11-20 Kevin P. Costello , Van Vu

A classical proposal to derive weights from a pairwise comparison matrix is the right eigenvector. The literature has identified some potential weaknesses of this method in previous decades. This chapter discusses five of these issues.…

Optimization and Control · Mathematics 2026-03-26 Sándor Bozóki , László Csató

In this article the well known "Perron-Frobenius theory" is investigated involving the higher rank numerical range $\Lambda_{k}(A)$ of an irreducible and entrywise nonnegative matrix $A$ and extending the notion of elements of maximum…

Rings and Algebras · Mathematics 2011-04-08 Aikaterini Aretaki , John Maroulas

We provide new upper and lower bounds on the minimum possible ratio of the spectral and Frobenius norms of a (partially) symmetric tensor. In the particular case of general tensors our result recovers a known upper bound. For symmetric…

Functional Analysis · Mathematics 2024-03-05 Khazhgali Kozhasov , Josué Tonelli-Cueto

We consider a notion of probabilistic rank and probabilistic sign-rank of a matrix, which measures the extent to which a matrix can be probabilistically represented by low-rank matrices. We demonstrate several connections with matrix…

Computational Complexity · Computer Science 2018-02-01 Josh Alman , Ryan Williams

We give upper bounds for the determinant of an $n\times n$ zero-one matrix containing $kn$ ones for integral $k$. Our results improve upon a result of Ryser for $k=o(n^{1/3})$. For fixed $k\ge 3$ it was an open question whether Hadamard's…

Combinatorics · Mathematics 2019-03-04 Daniel Scheinerman

This is a foundational paper in tropical linear algebra, which is linear algebra over the min-plus semiring. We introduce and compare three natural definitions of the rank of a matrix, called the Barvinok rank, the Kapranov rank and the…

Combinatorics · Mathematics 2007-05-23 M. Develin , F. Santos , B. Sturmfels

Multi-label ranking, which returns multiple top-ranked labels for each instance, has a wide range of applications for visual tasks. Due to its complicated setting, prior arts have proposed various measures to evaluate model performances.…

Machine Learning · Computer Science 2024-07-10 Zitai Wang , Qianqian Xu , Zhiyong Yang , Peisong Wen , Yuan He , Xiaochun Cao , Qingming Huang

Any homogeneous harmonic polynomial can be decomposed as a sum of powers of isotropic linear forms, that is, linear forms whose coefficients are the coordinates of isotropic points. The minimum size of such decompositions for a harmonic…

Algebraic Geometry · Mathematics 2025-12-08 S. Canino , C. Flavi

The problem of determining the set of possible eigenvalues of 3 Hermitian matrices that sum up to zero is known as the Horn problem. The answer is a polyhedral cone, which, following Knutson and Tao, can be described as the projection of a…

Combinatorics · Mathematics 2012-07-04 Anton Alekseev , Masha Podkopaeva , Andras Szenes

A common problem in machine learning is to rank a set of n items based on pairwise comparisons. Here ranking refers to partitioning the items into sets of pre-specified sizes according to their scores, which includes identification of the…

Machine Learning · Computer Science 2018-01-08 Reinhard Heckel , Max Simchowitz , Kannan Ramchandran , Martin J. Wainwright

In this paper, we establish a connection between ranking theory and general equilibrium theory. First of all, we show that the ranking vector of PageRank or Invariant method is precisely the equilibrium of a special Cobb-Douglas market.…

Computer Science and Game Theory · Computer Science 2009-10-06 Ye Du

We derive new comparison inequalities between weak and strong moments of norms of random vectors with optimal (up to an universal factor) constants. We discuss applications to the concentration of log-concave random vectors and bounds on…

Probability · Mathematics 2021-06-08 Rafał Latała , Piotr Nayar

Let $\mathbb{P}_G([0,\infty))$ and $\mathbb{P}_G^{'}([0,\infty))$ be the sets of positive semidefinite and positive definite matrices of order $n$, respectively, with nonnegative entries, where some positions of zero entries are restricted…

Combinatorics · Mathematics 2022-02-09 Veer Singh Panwar , A. Satyanarayana Reddy

We determine the rank of a random matrix over an arbitrary field with prescribed numbers of non-zero entries in each row and column. As an application we obtain a formula for the rate of low-density parity check codes. This formula…

Combinatorics · Mathematics 2024-06-21 Amin Coja-Oghlan , Alperen A. Ergür , Pu Gao , Samuel Hetterich , Maurice Rolvien

Estimating the linear dimensionality of a data set in the presence of noise is a common problem. However, data may also be corrupted by monotone nonlinear distortion that preserves the ordering of matrix entries but causes linear methods…

Combinatorics · Mathematics 2024-01-01 Caitlin Lienkaemper

The square root rank of a nonnegative matrix $A$ is the minimum rank of a matrix $B$ such that $A=B \circ B$, where $\circ$ denotes entrywise product. We show that the square root rank of the slack matrix of the correlation polytope is…

Computational Complexity · Computer Science 2014-11-26 Troy Lee , Zhaohui Wei