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We study applications of clustering (in particular, the $k$-center clustering problem) in the design of efficient and practical algorithms for computing an approximate and the exact arithmetic matrix product of two 0-1 rectangular matrices…

Data Structures and Algorithms · Computer Science 2025-12-30 Jesper Jansson , Miroslaw Kowaluk , Andrzej Lingas , Mia Persson

We consider the problem of reconstructing a rank-$k$ $n \times n$ matrix $M$ from a sampling of its entries. Under a certain incoherence assumption on $M$ and for the case when both the rank and the condition number of $M$ are bounded, it…

Machine Learning · Statistics 2017-08-23 David Gamarnik , Quan Li , Hongyi Zhang

The 1-product of matrices $S_1 \in \mathbb{R}^{m_1 \times n_1}$ and $S_2 \in \mathbb{R}^{m_2 \times n_2}$ is the matrix in $\mathbb{R}^{(m_1+m_2) \times (n_1n_2)}$ whose columns are the concatenation of each column of $S_1$ with each column…

Combinatorics · Mathematics 2020-02-07 Manuel Aprile , Michele Conforti , Yuri Faenza , Samuel Fiorini , Tony Huynh , Marco Macchia

Karppa & Kaski (2019) proposed a novel ``broken" or ``opportunistic" matrix multiplication algorithm, based on a variant of Strassen's algorithm, and used this to develop new algorithms for Boolean matrix multiplication, among other tasks.…

Data Structures and Algorithms · Computer Science 2024-09-05 David G. Harris

This paper establishes the exact comparison complexity of finding an element repeated $n$ times in a $2n$-element array containing $n+1$ distinct values, under the equality-comparison model with $O(1)$ extra space. We present a simple…

Data Structures and Algorithms · Computer Science 2026-02-09 Andrew Au

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

In this paper we provide an $\tilde{O}(nd+d^{3})$ time randomized algorithm for solving linear programs with $d$ variables and $n$ constraints with high probability. To obtain this result we provide a robust, primal-dual…

Data Structures and Algorithms · Computer Science 2021-08-24 Jan van den Brand , Yin Tat Lee , Aaron Sidford , Zhao Song

Classic cache-oblivious parallel matrix multiplication algorithms achieve optimality either in time or space, but not both, which promotes lots of research on the best possible balance or tradeoff of such algorithms. We study modern…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-14 Yuan Tang

Given some binary matrix $M$, suppose we are presented with the collection of its rows and columns in independent arbitrary orderings. From this information, are we able to recover the unique original orderings and matrix? We present an…

Probability · Mathematics 2024-04-24 Caelan Atamanchuk , Luc Devroye , Massimo Vicenzo

We study the problem of optimizing nonlinear objective functions over matroids presented by oracles or explicitly. Such functions can be interpreted as the balancing of multi-criteria optimization. We provide a combinatorial polynomial time…

Combinatorics · Mathematics 2008-07-24 Yael Berstein , Jon Lee , Hugo Maruri-Aguilar , Shmuel Onn , Eva Riccomagno , Robert Weismantel , Henry Wynn

A new procedure is presented for computing the matrix cosine and sine simultaneously by means of Taylor polynomial approximations. These are factorized so as to reduce the number of matrix products involved. Two versions are developed to be…

Numerical Analysis · Mathematics 2020-10-02 Muaz Seydaoglu , Philipp Bader , Sergio Blanes , Fernando Casas

We propose an efficient algorithm to numerically solve Anderson impurity problems using matrix product states. By introducing a modified chain mapping we obtain significantly lower entanglement, as compared to all previous attempts, while…

Strongly Correlated Electrons · Physics 2021-07-14 Lucas Kohn , Giuseppe E. Santoro

We give an algorithm for completing an order-$m$ symmetric low-rank tensor from its multilinear entries in time roughly proportional to the number of tensor entries. We apply our tensor completion algorithm to the problem of learning…

Data Structures and Algorithms · Computer Science 2015-11-25 Tselil Schramm , Benjamin Weitz

We present a $O(1)$-approximate fully dynamic algorithm for the $k$-median and $k$-means problems on metric spaces with amortized update time $\tilde O(k)$ and worst-case query time $\tilde O(k^2)$. We complement our theoretical analysis…

Data Structures and Algorithms · Computer Science 2023-10-27 Sayan Bhattacharya , Martín Costa , Silvio Lattanzi , Nikos Parotsidis

Motivated by applications in recommender systems, web search, social choice and crowdsourcing, we consider the problem of identifying the set of top $K$ items from noisy pairwise comparisons. In our setting, we are non-actively given $r$…

Data Structures and Algorithms · Computer Science 2016-05-13 Xi Chen , Sivakanth Gopi , Jieming Mao , Jon Schneider

We give two algorithms for output-sparse matrix multiplication (OSMM), the problem of multiplying two $n \times n$ matrices $A, B$ when their product $AB$ is promised to have at most $O(n^{\delta})$ many non-zero entries for a given value…

Data Structures and Algorithms · Computer Science 2025-08-15 Huck Bennett , Karthik Gajulapalli , Alexander Golovnev , Evelyn Warton

Matrix $M$ is {\em $k$-concise} if the finite entries of each column of $M$ consist of $k$ or less intervals of identical numbers. We give an $O(n+m)$-time algorithm to compute the row minima of any $O(1)$-concise $n\times m$ matrix. Our…

Data Structures and Algorithms · Computer Science 2014-03-04 Cheng-Wei Lee , Hsueh-I Lu

The product of a matrix chain consisting of $n$ matrices can be computed in $C_{n-1}$ (Catalan's number) different ways, each identified by a distinct parenthesisation of the chain. The best algorithm to select a parenthesisation that…

Discrete Mathematics · Computer Science 2025-04-08 Francisco López , Lars Karlsson , Paolo Bientinesi

In this paper we show how to recover a spectral approximations to broad classes of structured matrices using only a polylogarithmic number of adaptive linear measurements to either the matrix or its inverse. Leveraging this result we obtain…

Data Structures and Algorithms · Computer Science 2018-12-18 Arun Jambulapati , Kirankumar Shiragur , Aaron Sidford

Recently, Armstrong, Guzm\'an, and Sing Long (2021), presented an optimal $O(n^2)$ time algorithm for strict circular seriation (called also the recognition of strict quasi-circular Robinson spaces). In this paper, we give a very simple…

Discrete Mathematics · Computer Science 2023-05-23 Mikhael Carmona , Victor Chepoi , Guyslain Naves , Pascal Préa