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Online bipartite matching is a fundamental problem in online algorithms. The goal is to match two sets of vertices to maximize the sum of the edge weights, where for one set of vertices, each vertex and its corresponding edge weights appear…

Data Structures and Algorithms · Computer Science 2024-02-13 Hang Hu , Zhao Song , Runzhou Tao , Zhaozhuo Xu , Junze Yin , Danyang Zhuo

This paper examines linear binary codes capable of correcting one or more errors. For the single-error-correcting case, it is shown that the Hamming bound is achieved by a constructive method, and an exact expression for the minimal…

Information Theory · Computer Science 2025-12-16 Timofei Izhitskii

A matrix completion problem is to recover the missing entries in a partially observed matrix. Most of the existing matrix completion methods assume a low rank structure of the underlying complete matrix. In this paper, we introduce an…

Machine Learning · Statistics 2020-11-16 Chencheng Cai , Rong Chen , Han Xiao

We consider the problem of enumerating hypermatrices of format $2 \times (k + 1) \times k$ over a finite field that have nonzero hyperdeterminant and whose nonzero entries are restricted to a plane partition. We conjecture an attractive…

Combinatorics · Mathematics 2026-02-26 Brandon Koprowski , Joel Brewster Lewis

Submodular functions have many applications. Matchings have many applications. The bitext word alignment problem can be modeled as the problem of maximizing a nonnegative, monotone, submodular function constrained to matchings in a complete…

Data Structures and Algorithms · Computer Science 2013-01-14 Sagar Kale

Given an integer weighted bipartite graph $\{G=(U\sqcup V, E), w:E\rightarrow \mathbb{Z}\}$ we consider the problems of finding all the edges that occur in some minimum weight matching of maximum cardinality and enumerating all the minimum…

Combinatorics · Mathematics 2014-03-27 Carlos E. Valencia , Marcos C. Vargas

We study embeddings between reproducing kernel Hilbert spaces $H(K)$ of functions of $d \in \mathbb{N} \cup \{\infty\}$ variables. The kernels $K$ are superpositions of weighted finite tensor products of a fixed univariate kernel. The basic…

Numerical Analysis · Mathematics 2026-05-01 Michael Gnewuch , Peter Kritzer , Klaus Ritter

This paper proposes a generic formulation that significantly expedites the training and deployment of image classification models, particularly under the scenarios of many image categories and high feature dimensions. As a defining…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Fumin Shen , Yadong Mu , Wei Liu , Yang Yang , Heng Tao Shen

A zero-one matrix is a matrix with entries from $\{0, 1\}$. We study monoids containing only such matrices. A finite set of zero-one matrices generating such a monoid can be seen as the matrix representation of an unambiguous finite…

Formal Languages and Automata Theory · Computer Science 2025-11-14 Stefan Kiefer , Andrew Ryzhikov

We consider the decision problem asking whether a partial rational symmetric matrix with an all-ones diagonal can be completed to a full positive semidefinite matrix of rank at most $k$. We show that this problem is $\NP$-hard for any fixed…

Optimization and Control · Mathematics 2012-09-19 Marianna Eisenberg-Nagy , Monique Laurent , Antonios Varvitsiotis

For a graph $G$, let $Z(G,\lambda)$ be the partition function of the monomer-dimer system defined by $\sum_k m_k(G)\lambda^k$, where $m_k(G)$ is the number of matchings of size $k$ in $G$. We consider graphs of bounded degree and develop a…

Data Structures and Algorithms · Computer Science 2013-09-05 Marc Lelarge , Hang Zhou

Let n be an even positive integer and F be the field \GF(2). A word in F^n is called balanced if its Hamming weight is n/2. A subset C \subseteq F^n$ is called a balancing set if for every word y \in F^n there is a word x \in C such that y…

Information Theory · Computer Science 2010-12-17 Arya Mazumdar , Ron M. Roth , Pascal O. Vontobel

We consider the problem of noisy 1-bit matrix completion under an exact rank constraint on the true underlying matrix $M^*$. Instead of observing a subset of the noisy continuous-valued entries of a matrix $M^*$, we observe a subset of…

Machine Learning · Statistics 2015-02-25 Sonia Bhaskar , Adel Javanmard

The AWGNC, BSC, and max-fractional pseudocodeword redundancies of a binary linear code are defined to be the smallest number of rows in a parity-check matrix such that the corresponding minimum pseudoweight is equal to the minimum Hamming…

Information Theory · Computer Science 2012-03-07 Jens Zumbrägel , Vitaly Skachek , Mark F. Flanagan

We present a novel algebraic combinatorial view on low-rank matrix completion based on studying relations between a few entries with tools from algebraic geometry and matroid theory. The intrinsic locality of the approach allows for the…

Machine Learning · Computer Science 2014-08-20 Franz J. Király , Louis Theran , Ryota Tomioka

Rank weights and generalized rank weights have been proven to characterize error and erasure correction, and information leakage in linear network coding, in the same way as Hamming weights and generalized Hamming weights describe classical…

Information Theory · Computer Science 2016-04-25 Umberto Martínez-Peñas

We consider the problem of constructing deletion correcting codes over a binary alphabet and take a graph theoretic view. An $n$-bit $s$-deletion correcting code is an independent set in a particular graph. We propose constructing such a…

Information Theory · Computer Science 2012-11-20 Daniel Cullina , Ankur A. Kulkarni , Negar Kiyavash

By a tensor we mean an element of a tensor product of vector spaces over a field. Up to a choice of bases in factors of tensor products, every tensor may be coordinatized, that is, represented as an array consisting of numbers. This note is…

Functional Analysis · Mathematics 2019-01-11 R. N. Gumerov , A. S. Sharafutdinov

Despite the popularity of low-rank matrix completion, the majority of its theory has been developed under the assumption of random observation patterns, whereas very little is known about the practically relevant case of non-random…

Machine Learning · Computer Science 2023-02-24 Manolis C. Tsakiris

In conventional prediction tasks, a machine learning algorithm outputs a single best model that globally optimizes its objective function, which typically is accuracy. Therefore, users cannot access the other models explicitly. In contrast…

Machine Learning · Computer Science 2019-06-06 Kentaro Kanamori , Satoshi Hara , Masakazu Ishihata , Hiroki Arimura