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We prove, using the subspace embedding guarantee in a black box way, that one can achieve the spectral norm guarantee for approximate matrix multiplication with a dimensionality-reducing map having $m = O(\tilde{r}/\varepsilon^2)$ rows.…

Data Structures and Algorithms · Computer Science 2016-03-03 Michael B. Cohen , Jelani Nelson , David P. Woodruff

We show that Boolean matrix multiplication, computed as a sum of products of column vectors with row vectors, is essentially the same as Warshall's algorithm for computing the transitive closure matrix of a graph from its adjacency matrix.…

Discrete Mathematics · Computer Science 2017-11-08 Michiel de Bondt

An ordered binary decision diagram (OBDD) is a directed acyclic graph that represents a Boolean function. OBDDs are also known as special cases of oblivious read-once branching programs in the field of complexity theory. Since OBDDs have…

Quantum Physics · Physics 2025-05-19 Seiichiro Tani

Min-plus product of two $n\times n$ matrices is a fundamental problem in algorithm research. It is known to be equivalent to APSP, and in general it has no truly subcubic algorithms. In this paper, we focus on the min-plus product on a…

Data Structures and Algorithms · Computer Science 2022-02-03 Shucheng Chi , Ran Duan , Tianle Xie

The ultimate goal of any numerical scheme for partial differential equations (PDEs) is to compute an approximation of user-prescribed accuracy at quasi-minimal computational time. To this end, algorithmically, the standard adaptive finite…

Numerical Analysis · Mathematics 2025-01-30 Philipp Bringmann , Michael Feischl , Ani Miraci , Dirk Praetorius , Julian Streitberger

We consider the problem of reconstructing a low rank matrix from a subset of its entries and analyze two variants of the so-called Alternating Minimization algorithm, which has been proposed in the past. We establish that when the…

Machine Learning · Statistics 2016-09-21 David Gamarnik , Sidhant Misra

We give a polynomial time algorithm to decode multivariate polynomial codes of degree $d$ up to half their minimum distance, when the evaluation points are an arbitrary product set $S^m$, for every $d < |S|$. Previously known algorithms can…

Computational Complexity · Computer Science 2015-11-25 John Kim , Swastik Kopparty

Counting $(p,q)$-bicliques in bipartite graphs is crucial for a variety of applications, from recommendation systems to cohesive subgraph analysis. Yet, it remains computationally challenging due to the combinatorial explosion to exactly…

Social and Information Networks · Computer Science 2025-12-09 Jingbang Chen , Weinuo Li , Yingli Zhou , Hangrui Zhou , Qiuyang Mang , Can Wang , Yixiang Fang , Chenhao Ma

We consider $\ell_1$-Rank-$r$ Approximation over GF(2), where for a binary $m\times n$ matrix ${\bf A}$ and a positive integer $r$, one seeks a binary matrix ${\bf B}$ of rank at most $r$, minimizing the column-sum norm $||{\bf A} -{\bf…

Data Structures and Algorithms · Computer Science 2019-04-15 Fedor V. Fomin , Petr A. Golovach , Fahad Panolan , Kirill Simonov

Boolean matrix factorization is a natural and a popular technique for summarizing binary matrices. In this paper, we study a problem of Boolean matrix factorization where we additionally require that the factor matrices have consecutive…

Data Structures and Algorithms · Computer Science 2019-05-16 Nikolaj Tatti , Pauli Miettinen

Maximum bipartite matching (MBM) is a fundamental problem in combinatorial optimization with a long and rich history. A classic result of Hopcroft and Karp (1973) provides an $O(m \sqrt{n})$-time algorithm for the problem, where $n$ and $m$…

Data Structures and Algorithms · Computer Science 2024-06-03 Julia Chuzhoy , Sanjeev Khanna

We consider the problem of computing the nearest matrix polynomial with a non-trivial Smith Normal Form. We show that computing the Smith form of a matrix polynomial is amenable to numeric computation as an optimization problem.…

Symbolic Computation · Computer Science 2019-09-10 Mark Giesbrecht , Joseph Haraldson , George Labahn

Given a dissimilarity matrix, the metric nearness problem is to find the nearest matrix of distances that satisfy the triangle inequalities. This problem has wide applications, such as sensor networks, image processing, and so on. But it is…

Optimization and Control · Mathematics 2022-11-03 Peipei Tang , Bo Jiang , Chengjing Wang

The Monotone Min-Plus Product problem is a useful primitive that has seen many algorithmic applications over the past decade. In this problem, we are given two $n\times n$ integer matrices $A$ and $B$, where each row of $B$ is a monotone…

Data Structures and Algorithms · Computer Science 2026-05-11 Ce Jin , Jaewoo Park , Barna Saha , Yinzhan Xu

Let $P$ be a set of at most $n$ points and let $R$ be a set of at most $n$ geometric ranges, such as for example disks or rectangles, where each $p \in P$ has an associated supply $s_{p} > 0$, and each $r \in R$ has an associated demand…

Computational Geometry · Computer Science 2023-12-05 Sergio Cabello , Siu-Wing Cheng , Otfried Cheong , Christian Knauer

In this paper we consider parallel implementations of approximate multiplication of large matrices with exponential decay of elements. Such matrices arise in computations related to electronic structure calculations and some other fields of…

Numerical Analysis · Mathematics 2021-02-23 Anton G. Artemov

We propose an algorithm for generating explicit solutions of multiparametric mixed-integer convex programs to within a given suboptimality tolerance. The algorithm is applicable to a very general class of optimization problems, but is most…

Optimization and Control · Mathematics 2019-06-12 Danylo Malyuta , Behcet Acikmese

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have…

Data Structures and Algorithms · Computer Science 2011-03-21 Philip Bille

Identifying discrete patterns in binary data is an important dimensionality reduction tool in machine learning and data mining. In this paper, we consider the problem of low-rank binary matrix factorisation (BMF) under Boolean arithmetic.…

Optimization and Control · Mathematics 2021-08-05 Reka A. Kovacs , Oktay Gunluk , Raphael A. Hauser

Two simple yet powerful optimization algorithms, named the Best-Mean-Random (BMR) and Best-Worst-Random (BWR) algorithms, are developed and presented in this paper to handle both constrained and unconstrained optimization problems. These…

Neural and Evolutionary Computing · Computer Science 2024-09-10 Ravipudi Venkata Rao , Ravikumar shah