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For "large" class $\mathcal{C}$ of continuous probability density functions (p.d.f.), we demonstrate that for every $w\in\mathcal{C}$ there is mixture of discrete Binomial distributions (MDBD) with $T\geq N\sqrt{\phi_{w}/\delta}$ distinct…

Discrete Mathematics · Computer Science 2016-04-22 Gorav Jindal , Pavel Kolev

We consider the following general hidden hubs model: an $n \times n$ random matrix $A$ with a subset $S$ of $k$ special rows (hubs): entries in rows outside $S$ are generated from the probability distribution $p_0 \sim N(0,\sigma_0^2)$; for…

Machine Learning · Computer Science 2016-11-17 Ravi Kannan , Santosh Vempala

We give a proof of the conjecture of Nelson and Nguyen [FOCS 2013] on the optimal dimension and sparsity of oblivious subspace embeddings, up to sub-polylogarithmic factors: For any $n\geq d$ and $\epsilon\geq d^{-O(1)}$, there is a random…

Data Structures and Algorithms · Computer Science 2025-11-18 Shabarish Chenakkod , Michał Dereziński , Xiaoyu Dong

Strongly Rayleigh distributions are a class of negatively dependent distributions of binary-valued random variables [Borcea, Branden, Liggett JAMS 09]. Recently, these distributions have played a crucial role in the analysis of algorithms…

Probability · Mathematics 2018-10-22 Rasmus Kyng , Zhao Song

We present a nearly-linear time algorithm that produces high-quality sparsifiers of weighted graphs. Given as input a weighted graph $G=(V,E,w)$ and a parameter $\epsilon>0$, we produce a weighted subgraph $H=(V,\tilde{E},\tilde{w})$ of $G$…

Data Structures and Algorithms · Computer Science 2009-11-18 Daniel A. Spielman , Nikhil Srivastava

Motivated by the problem of fast processing of attention matrices, we study fast algorithms for computing matrix-vector products for asymmetric Gaussian Kernel matrices $K\in \mathbb{R}^{n\times n}$. $K$'s columns are indexed by a set of…

Machine Learning · Computer Science 2025-08-01 Piotr Indyk , Michael Kapralov , Kshiteej Sheth , Tal Wagner

A seminal work of [Ahn-Guha-McGregor, PODS'12] showed that one can compute a cut sparsifier of an unweighted undirected graph by taking a near-linear number of linear measurements on the graph. Subsequent works also studied computing other…

Data Structures and Algorithms · Computer Science 2022-09-19 Yu Chen , Sanjeev Khanna , Huan Li

We study the spectral properties of a class of random matrices of the form $S_n^{-} = n^{-1}(X_1 X_2^* - X_2 X_1^*)$ where $X_k = \Sigma^{1/2}Z_k$, for $k=1,2$, $Z_k$'s are independent $p\times n$ complex-valued random matrices, and…

Statistics Theory · Mathematics 2024-11-27 Javed Hazarika , Debashis Paul

We give an algorithm for computing approximate PSD factorizations of nonnegative matrices. The running time of the algorithm is polynomial in the dimensions of the input matrix, but exponential in the PSD rank and the approximation error.…

Data Structures and Algorithms · Computer Science 2016-02-25 Amitabh Basu , Michael Dinitz , Xin Li

This paper presents the first parallel batch-dynamic algorithms for computing spanners and sparsifiers. Our algorithms process any batch of edge insertions and deletions in an $n$-node undirected graph, in $\text{poly}(\log n)$ depth and…

Data Structures and Algorithms · Computer Science 2025-07-10 Mohsen Ghaffari , Jaehyun Koo

In this paper, we prove convergence rates for time discretisation schemes for semi-linear stochastic evolution equations with additive or multiplicative Gaussian noise, where the leading operator $A$ is the generator of a strongly…

Numerical Analysis · Mathematics 2024-12-19 Katharina Klioba , Mark Veraar

We consider the action of the $q$-deformed Poincar\'e superalgebra on the massless non-relativistic R-matrix in ordinary (undeformed) integrable $AdS_2 \times S^2 \times T^6$ type IIB superstring theory. The boost generator acts…

High Energy Physics - Theory · Physics 2022-10-12 Andrea Fontanella , Alessandro Torrielli

We present the first parallel algorithm for solving systems of linear equations in symmetric, diagonally dominant (SDD) matrices that runs in polylogarithmic time and nearly-linear work. The heart of our algorithm is a construction of a…

Numerical Analysis · Computer Science 2013-11-14 Richard Peng , Daniel A. Spielman

We give a simple proof of the matrix Spencer conjecture up to poly-logarithmic rank: given symmetric $d \times d$ matrices $A_1,\ldots,A_n$ each with $\|A_i\|_{\mathsf{op}} \leq 1$ and rank at most $n/\log^3 n$, one can efficiently find…

Data Structures and Algorithms · Computer Science 2022-08-30 Nikhil Bansal , Haotian Jiang , Raghu Meka

We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization…

Probability · Mathematics 2024-01-03 Laura Shou , Ramon van Handel

We consider a basic computational task of finding $s$ planted rank-1 $m \times n$ matrices in a linear subspace $\mathcal{U} \subseteq \mathbb{R}^{m \times n}$ where $\dim(\mathcal{U}) = R \ge s$. The work of Johnston-Lovitz-Vijayaraghavan…

Data Structures and Algorithms · Computer Science 2025-04-28 Jeshu Dastidar , Tait Weicht , Alexander S. Wein

This paper considers the problem of positive semidefinite factorization (PSD factorization), a generalization of exact nonnegative matrix factorization. Given an $m$-by-$n$ nonnegative matrix $X$ and an integer $k$, the PSD factorization…

Optimization and Control · Mathematics 2018-08-29 Arnaud Vandaele , François Glineur , Nicolas Gillis

Let $H_n$ be a graph on $n$ vertices and let $\ber{H_n}$ denote the complement of $H_n$. Suppose that $\Delta = \Delta(n)$ is the maximum degree of $\ber{H_n}$. We analyse three algorithms for sampling $d$-regular subgraphs ($d$-factors) of…

Combinatorics · Mathematics 2019-10-25 Pu Gao , Catherine Greenhill

The eigenvalues and eigenvectors of nonnormal matrices can be unstable under perturbations of their entries. This renders an obstacle to the analysis of numerical algorithms for non-Hermitian eigenvalue problems. A recent technique to…

Probability · Mathematics 2026-04-14 Rikhav Shah , Nikhil Srivastava , Edward Zeng

Hankel matrices are an important class of highly-structured matrices, arising across computational mathematics, engineering, and theoretical computer science. It is well-known that positive semidefinite (PSD) Hankel matrices are always…

Data Structures and Algorithms · Computer Science 2025-11-27 Michael Kapralov , Cameron Musco , Kshiteej Sheth