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Randomized algorithms are overwhelming methods for low-rank approximation that can alleviate the computational expenditure with great reliability compared to deterministic algorithms. A crucial thought is generating a standard Gaussian…

Computation · Statistics 2025-06-05 Dandan Jiang , Bo Fu , Weiwei Xu

A tight $\Omega((n/\sqrt{M})^{\log_2 7}M)$ lower bound is derived on the \io complexity of Strassen's algorithm to multiply two $n \times n$ matrices, in a two-level storage hierarchy with $M$ words of fast memory. A proof technique is…

Data Structures and Algorithms · Computer Science 2016-05-10 Gianfranco Bilardi , Lorenzo De Stefani

Many combinatorial optimization problems can be formulated as the search for a subgraph that satisfies certain properties and minimizes the total weight. We assume here that the vertices correspond to points in a metric space and can take…

Data Structures and Algorithms · Computer Science 2024-12-25 Marin Bougeret , Jérémy Omer , Michael Poss

Regularized risk minimization with the binary hinge loss and its variants lies at the heart of many machine learning problems. Bundle methods for regularized risk minimization (BMRM) and the closely related SVMStruct are considered the best…

Machine Learning · Computer Science 2009-09-09 Ankan Saha , Xinhua Zhang , S. V. N. Vishwanathan

The maximum bipartite matching problem is among the most fundamental and well-studied problems in combinatorial optimization. A beautiful and celebrated combinatorial algorithm of Hopcroft and Karp (1973) shows that maximum bipartite…

Data Structures and Algorithms · Computer Science 2023-12-21 Julia Chuzhoy , Sanjeev Khanna

We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. We consider models of agent behaviour in which they either…

Computer Science and Game Theory · Computer Science 2009-10-01 Brendan Lucier

Addressing the interpretability problem of NMF on Boolean data, Boolean Matrix Factorization (BMF) uses Boolean algebra to decompose the input into low-rank Boolean factor matrices. These matrices are highly interpretable and very useful in…

Machine Learning · Computer Science 2023-07-18 Sebastian Dalleiger , Jilles Vreeken

We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pal and Vondrak, 2008), our algorithm is…

Data Structures and Algorithms · Computer Science 2013-11-20 Yuval Filmus , Justin Ward

A major goal in the area of exact exponential algorithms is to give an algorithm for the (worst-case) $n$-input Subset Sum problem that runs in time $2^{(1/2 - c)n}$ for some constant $c>0$. In this paper we give a Subset Sum algorithm with…

Data Structures and Algorithms · Computer Science 2023-01-31 Xi Chen , Yaonan Jin , Tim Randolph , Rocco A. Servedio

Sublinear time algorithms for approximating maximum matching size have long been studied. Much of the progress over the last two decades on this problem has been on the algorithmic side. For instance, an algorithm of Behnezhad [FOCS'21]…

Data Structures and Algorithms · Computer Science 2022-11-30 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

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

The Boolean Hidden Matching (BHM) problem, introduced in a seminal paper of Gavinsky et. al. [STOC'07], has played an important role in the streaming lower bounds for graph problems such as triangle and subgraph counting, maximum matching,…

Data Structures and Algorithms · Computer Science 2022-01-31 Michael Kapralov , Amulya Musipatla , Jakab Tardos , David P. Woodruff , Samson Zhou

It is known that a better than $2$-approximation algorithm for the girth in dense directed unweighted graphs needs $n^{3-o(1)}$ time unless one uses fast matrix multiplication. Meanwhile, the best known approximation factor for a…

Data Structures and Algorithms · Computer Science 2020-04-28 Mina Dalirrooyfard , Virginia Vassilevska Williams

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

We propose an incomplete algorithm for Maximum Satisfiability (MaxSAT) specifically designed to run on neural network accelerators such as GPUs and TPUs. Given a MaxSAT problem instance in conjunctive normal form, our procedure constructs a…

Artificial Intelligence · Computer Science 2023-11-07 David Warde-Farley , Vinod Nair , Yujia Li , Ivan Lobov , Felix Gimeno , Simon Osindero

We consider fast algorithms for monotone submodular maximization with a general matroid constraint. We present a randomized $(1 - 1/e - \epsilon)$-approximation algorithm that requires $\tilde{O}_{\epsilon}(\sqrt{r} n)$ independence oracle…

Data Structures and Algorithms · Computer Science 2024-05-02 Yusuke Kobayashi , Tatsuya Terao

We show, for the input vectors $(a_0, a_1, ..., a_{n-1})$ and $(b_0, b_1, ..., b_{n-1})$, where $a_i$'s and $b_j$'s are real numbers, after $O(n\log^4 n)$ time preprocessing for each of them, the vector multiplication $(a_0, a_1, ...,…

Data Structures and Algorithms · Computer Science 2023-07-11 Yijie Han

Recently we have developed a new method in graph theory based on the Regularity Lemma. The method is applied to find certain spanning subgraphs in dense graphs. The other main general tool of the method, beside the Regularity Lemma, is the…

Combinatorics · Mathematics 2016-09-07 János Komlós , Gabor N. Sarkozy , Endre Szemerédi

Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations. In this paper we show that \alpha>0.30298, which improves the previous…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall

After Strassen presented the first sub-cubic matrix multiplication algorithm, many Strassen-like algorithms are presented. Most of them with low asymptotic cost have large hidden leading coefficient which are thus impractical. To reduce the…

Symbolic Computation · Computer Science 2022-03-31 Pu Wu , Huiqing Jiang , Zehui Shao , Jin Xu
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