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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

This paper introduces the \emph{$d$-distance matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges and an integer $d\in\mathbb Z_+$. The goal is to find a maximum…

Combinatorics · Mathematics 2023-01-24 Péter Madarasi

While leverage score sampling provides powerful tools for approximating solutions to large least squares problems, the cost of computing exact scores and sampling often prohibits practical application. This paper addresses this challenge by…

Numerical Analysis · Mathematics 2025-04-29 Osman Asif Malik , Yiming Xu , Nuojin Cheng , Stephen Becker , Alireza Doostan , Akil Narayan

There has been growing attention on how to effectively and objectively use covariate information when the primary goal is to estimate the average treatment effect (ATE) in randomized clinical trials (RCTs). In this paper, we propose an…

Methodology · Statistics 2020-09-01 Yuanyao Tan , Xialing Wen , Wei Liang , Ying Yan

Low-rank matrix completion is an important problem with extensive real-world applications. When observations are uniformly sampled from the underlying matrix entries, existing methods all require the matrix to be incoherent. This paper…

Machine Learning · Computer Science 2015-02-11 Shusen Wang , Tong Zhang , Zhihua Zhang

This article concerns the computational problem of counting the lattice points inside convex polytopes, when each point must be counted with a weight associated to it. We describe an efficient algorithm for computing the highest degree…

Combinatorics · Mathematics 2010-11-09 Velleda Baldoni , Nicole Berline , Jesús A. De Loera , Matthias Köppe , Michèle Vergne

We study linear polynomial approximation of functions in weighted Sobolev spaces $W^r_{p,w}(\mathbb{R}^d)$ of mixed smoothness $r \in \mathbb{N}$, and their optimality in terms of Kolmogorov and linear $n$-widths of the unit ball…

Numerical Analysis · Mathematics 2025-01-03 Dinh Dũng

Rips complexes are important structures for analyzing topological features of metric spaces. Unfortunately, generating these complexes is expensive because of a combinatorial explosion in the complex size. For $n$ points in $\mathbb{R}^d$,…

Computational Geometry · Computer Science 2021-05-12 Aruni Choudhary , Michael Kerber , Sharath Raghvendra

The Weighted Tree Augmentation Problem (WTAP) is a fundamental network design problem where the goal is to find a minimum-cost set of additional edges (links) to make an input tree 2-edge-connected. While a 2-approximation is standard and…

Data Structures and Algorithms · Computer Science 2026-04-01 Vincent Cohen-Addad , Marina Drygala , Nathan Klein , Ola Svensson

The main purpose of this paper is to investigate the strong approximation of the $p$-fold integrated empirical process, $p$ being a fixed positive integer. More precisely, we obtain the exact rate of the approximations by a sequence of…

Statistics Theory · Mathematics 2019-03-15 Sergio Alvarez-Andrade , Salim Bouzebda , Aimé Lachal

Motivated by economic dispatch and linearly-constrained resource allocation problems, this paper proposes a class of novel Distributed-Approx Newton algorithms that approximate the standard Newton optimization method. We first develop the…

Optimization and Control · Mathematics 2019-11-21 Tor Anderson , Chin-Yao Chang , Sonia Martinez

We present a new algorithm for reconstructing an exact algebraic number from its approximate value using an improved parameterized integer relation construction method. Our result is consistent with the existence of error controlling on…

Computational Complexity · Computer Science 2009-02-06 Xiaolin Qin , Yong Feng , Jingwei Chen , Jingzhong Zhang

Consider a random graph model where each possible edge $e$ is present independently with some probability $p_e$. Given these probabilities, we want to build a large/heavy matching in the randomly generated graph. However, the only way we…

Data Structures and Algorithms · Computer Science 2010-09-01 Nikhil Bansal , Anupam Gupta , Jian Li , Julian Mestre , Viswanath Nagarajan , Atri Rudra

The classical low rank approximation problem is to find a rank $k$ matrix $UV$ (where $U$ has $k$ columns and $V$ has $k$ rows) that minimizes the Frobenius norm of $A - UV$. Although this problem can be solved efficiently, we study an…

Data Structures and Algorithms · Computer Science 2019-11-20 Frank Ban , David Woodruff , Qiuyi Zhang

We provide fast algorithms for overconstrained $\ell_p$ regression and related problems: for an $n\times d$ input matrix $A$ and vector $b\in\mathbb{R}^n$, in $O(nd\log n)$ time we reduce the problem $\min_{x\in\mathbb{R}^d} \|Ax-b\|_p$ to…

Data Structures and Algorithms · Computer Science 2014-04-08 Kenneth L. Clarkson , Petros Drineas , Malik Magdon-Ismail , Michael W. Mahoney , Xiangrui Meng , David P. Woodruff

In a recent work, Esmer et al. describe a simple method - Approximate Monotone Local Search - to obtain exponential approximation algorithms from existing parameterized exact algorithms, polynomial-time approximation algorithms and, more…

Data Structures and Algorithms · Computer Science 2023-08-30 Baris Can Esmer , Ariel Kulik , Daniel Marx , Daniel Neuen , Roohani Sharma

We consider a novel challenge: approximating a distribution without the ability to randomly sample from that distribution. We study how such an approximation can be obtained using *weight queries*. Given some data set of examples, a weight…

Machine Learning · Computer Science 2021-07-15 Nadav Barak , Sivan Sabato

We present a subset selection algorithm designed to work with arbitrary model families in a practical batch setting. In such a setting, an algorithm can sample examples one at a time but, in order to limit overhead costs, is only able to…

Machine Learning · Computer Science 2023-01-31 Gui Citovsky , Giulia DeSalvo , Sanjiv Kumar , Srikumar Ramalingam , Afshin Rostamizadeh , Yunjuan Wang

We present faster high-accuracy algorithms for computing $\ell_p$-norm minimizing flows. On a graph with $m$ edges, our algorithm can compute a $(1+1/\text{poly}(m))$-approximate unweighted $\ell_p$-norm minimizing flow with…

Data Structures and Algorithms · Computer Science 2020-01-10 Deeksha Adil , Sushant Sachdeva

We study the worst-case approximation of multivariate periodic functions from the weighted Korobov space $H_{d,\alpha,\gamma}$ with smoothness $\alpha>1/2$ in the Lebesgue norm $L_p([0,1]^d)$ for $1\le p\le\infty$. We analyze a \emph{median…

Numerical Analysis · Mathematics 2026-03-06 Zexin Pan , Mou Cai , Josef Dick , Takashi Goda , Peter Kritzer