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Given a multiset $S$ of $n$ positive integers and a target integer $t$, the Subset Sum problem asks to determine whether there exists a subset of $S$ that sums up to $t$. The current best deterministic algorithm, by Koiliaris and Xu…

Data Structures and Algorithms · Computer Science 2020-01-03 Ce Jin , Hongxun Wu

Quantum one-class support vector machines leverage the advantage of quantum kernel methods for semi-supervised anomaly detection. However, their quadratic time complexity with respect to data size poses challenges when dealing with large…

Consider positive integral solutions $x \in \mathbb{Z}^{n+1}$ to the equation $a_0 x_0 + \ldots + a_n x_n = t$. In the so called unbounded subset sum problem, the objective is to decide whether such a solution exists, whereas in the…

Data Structures and Algorithms · Computer Science 2021-08-13 Kim-Manuel Klein

Consider a system of $m$ polynomial equations $\{p_i(x) = b_i\}_{i \leq m}$ of degree $D\geq 2$ in $n$-dimensional variable $x \in \mathbb{R}^n$ such that each coefficient of every $p_i$ and $b_i$s are chosen at random and independently…

Computational Complexity · Computer Science 2021-10-19 Jun-Ting Hsieh , Pravesh K. Kothari

Low-rank approximation is a common tool used to accelerate kernel methods: the $n \times n$ kernel matrix $K$ is approximated via a rank-$k$ matrix $\tilde K$ which can be stored in much less space and processed more quickly. In this work…

Data Structures and Algorithms · Computer Science 2017-11-07 Cameron Musco , David P. Woodruff

In the present paper we study a non-modular variant of the Short Integer Solution problem over the integers. Given a random matrix $A \in \mathbb{Z}^{n\times m}$ with entries $a_{ij}$ such that $0\le a_{ij}< Q,$ for some $Q>0,$ the goal is…

Cryptography and Security · Computer Science 2026-03-10 Konstantinos A. Draziotis , Myrto Eleftheria Gkogkou

Quantum Search Algorithm made a big impact by being able to solve the search problem for a set with $N$ elements using only $O(\sqrt{N})$ steps. Unfortunately, it is impossible to reduce the order of the complexity of this problem, however,…

Quantum Physics · Physics 2022-07-25 Umut Çalıkyılmaz , Sadi Turgut

Since Grover's seminal work, quantum search has been studied in great detail. In the usual search problem, we have a collection of n items and we would like to find a marked item. We consider a new variant of this problem in which…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

We give a new general approach for designing exact exponential-time algorithms for subset problems. In a subset problem the input implicitly describes a family of sets over a universe of size n and the task is to determine whether the…

Data Structures and Algorithms · Computer Science 2015-12-08 Fedor V. Fomin , Serge Gaspers , Daniel Lokshtanov , Saket Saurabh

In this work, we analyze a sublinear-time algorithm for selecting a few rows and columns of a matrix for low-rank approximation purposes. The algorithm is based on an initial uniformly random selection of rows and columns, followed by a…

Numerical Analysis · Mathematics 2024-02-22 Alice Cortinovis , Lexing Ying

In the classical Subset Sum problem we are given a set $X$ and a target $t$, and the task is to decide whether there exists a subset of $X$ which sums to $t$. A recent line of research has resulted in $\tilde{O}(t)$-time algorithms, which…

Data Structures and Algorithms · Computer Science 2023-04-25 Karl Bringmann , Vasileios Nakos

We study the $\ell_0$-Low Rank Approximation Problem, where the goal is, given an $m \times n$ matrix $A$, to output a rank-$k$ matrix $A'$ for which $\|A'-A\|_0$ is minimized. Here, for a matrix $B$, $\|B\|_0$ denotes the number of its…

Data Structures and Algorithms · Computer Science 2018-10-02 Karl Bringmann , Pavel Kolev , David P. Woodruff

We describe an algorithm for sampling a low-rank random matrix $Q$ that best approximates a fixed target matrix $P\in\mathbb{C}^{n\times m}$ in the following sense: $Q$ is unbiased, i.e., $\mathbb{E}[Q] = P$; $\mathsf{rank}(Q)\leq r$; and…

Data Structures and Algorithms · Computer Science 2026-03-18 Leighton Pate Barnes , Stephen Cameron , Benjamin Howard

We consider the quantum complexity of estimating matrix elements of unitary irreducible representations of groups. For several finite groups including the symmetric group, quantum Fourier transforms yield efficient solutions to this…

Quantum Physics · Physics 2009-04-21 Stephen P. Jordan

A new class of structured codes called Quasi Group Codes (QGC) is introduced. A QGC is a subset of a group code. In contrast with group codes, QGCs are not closed under group addition. The parameters of the QGC can be chosen such that the…

Information Theory · Computer Science 2017-08-03 Mohsen Heidari , Farhad Shirani , Sandeep Pradhan

Matrix geometric means between two positive definite matrices can be defined from distinct perspectives - as solutions to certain nonlinear systems of equations, as points along geodesics in Riemannian geometry, and as solutions to certain…

Quantum Physics · Physics 2025-06-23 Nana Liu , Qisheng Wang , Mark M. Wilde , Zhicheng Zhang

We study quantum algorithms for approximating Lasserre's hierarchy values for polynomial optimization. Let $f,g_1,\ldots,g_m$ be real polynomials in $n$ variables and $f^\star$ the infimum of $f$ over the semialgebraic set $S(g)=\{x:…

Quantum Physics · Physics 2025-11-19 Daniel Stilck França , Ngoc Hoang Anh Mai

Here, we give an algorithm for deciding if the nonnegative rank of a matrix $M$ of dimension $m \times n$ is at most $r$ which runs in time $(nm)^{O(r^2)}$. This is the first exact algorithm that runs in time singly-exponential in $r$. This…

Data Structures and Algorithms · Computer Science 2012-05-02 Ankur Moitra

In the Categorical Clustering problem, we are given a set of vectors (matrix) A={a_1,\ldots,a_n} over \Sigma^m, where \Sigma is a finite alphabet, and integers k and B. The task is to partition A into k clusters such that the median…

Data Structures and Algorithms · Computer Science 2021-04-19 Fedor V. Fomin , Petr A. Golovach , Nidhi Purohit

A fundamental problem arising in many applications in Web science and social network analysis is, given an arbitrary approximation factor $c>1$, to output a set $S$ of nodes that with high probability contains all nodes of PageRank at least…

Data Structures and Algorithms · Computer Science 2015-03-20 Christian Borgs , Michael Brautbar , Jennifer Chayes , Shang-Hua Teng
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