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The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new…

Data Structures and Algorithms · Computer Science 2009-07-10 Manjish Pal

In the stochastic online vector balancing problem, vectors $v_1,v_2,\ldots,v_T$ chosen independently from an arbitrary distribution in $\mathbb{R}^n$ arrive one-by-one and must be immediately given a $\pm$ sign. The goal is to keep the norm…

Data Structures and Algorithms · Computer Science 2020-07-22 Nikhil Bansal , Haotian Jiang , Raghu Meka , Sahil Singla , Makrand Sinha

The classical center based clustering problems such as $k$-means/median/center assume that the optimal clusters satisfy the locality property that the points in the same cluster are close to each other. A number of clustering problems arise…

Data Structures and Algorithms · Computer Science 2015-04-13 Anup Bhattacharya , Ragesh Jaiswal , Amit Kumar

We consider the SUBSET SUM problem and its important variants in this paper. In the SUBSET SUM problem, a (multi-)set $X$ of $n$ positive numbers and a target number $t$ are given, and the task is to find a subset of $X$ with the maximal…

Data Structures and Algorithms · Computer Science 2022-12-07 Xiaoyu Wu , Lin Chen

We present an $\mathcal{O}^\star(2^{0.5n})$ time and $\mathcal{O}^\star(2^{0.249999n})$ space randomized algorithm for solving worst-case Subset Sum instances with $n$ integers. This is the first improvement over the long-standing…

Data Structures and Algorithms · Computer Science 2021-04-13 Jesper Nederlof , Karol Węgrzycki

Learning from data in the presence of outliers is a fundamental problem in statistics. Until recently, no computationally efficient algorithms were known to compute the mean of a high dimensional distribution under natural assumptions in…

Data Structures and Algorithms · Computer Science 2021-01-22 Yeshwanth Cherapanamjeri , Sidhanth Mohanty , Morris Yau

We study sublinear time algorithms for estimating the size of maximum matching. After a long line of research, the problem was finally settled by Behnezhad [FOCS'22], in the regime where one is willing to pay an approximation factor of $2$.…

Data Structures and Algorithms · Computer Science 2023-04-28 Sayan Bhattacharya , Peter Kiss , Thatchaphol Saranurak

On sparse graphs, Roditty and Williams [2013] proved that no $O(n^{2-\varepsilon})$-time algorithm achieves an approximation factor smaller than $\frac{3}{2}$ for the diameter problem unless SETH fails. In this article, we solve an open…

Data Structures and Algorithms · Computer Science 2023-01-24 Pierre Bergé , Guillaume Ducoffe , Michel Habib

An important theorem of Banaszczyk (Random Structures & Algorithms `98) states that for any sequence of vectors of $\ell_2$ norm at most $1/5$ and any convex body $K$ of Gaussian measure $1/2$ in $\mathbb{R}^n$, there exists a signed…

Data Structures and Algorithms · Computer Science 2016-12-14 Daniel Dadush , Shashwat Garg , Shachar Lovett , Aleksandar Nikolov

Least-mean squares (LMS) solvers such as Linear / Ridge / Lasso-Regression, SVD and Elastic-Net not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as decision trees and…

Machine Learning · Computer Science 2020-09-08 Alaa Maalouf , Ibrahim Jubran , Dan Feldman

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 study a broad class of algorithmic problems with an "additive flavor" such as computing sumsets, 3SUM, Subset Sum and geometric pattern matching. Our starting point is that these problems can often be solved efficiently for integers,…

Data Structures and Algorithms · Computer Science 2024-10-30 Nick Fischer

The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new…

Data Structures and Algorithms · Computer Science 2010-11-22 Manjish Pal

In the Orthogonal Vectors problem (OV), we are given two families $A, B$ of subsets of $\{1,\ldots,d\}$, each of size $n$, and the task is to decide whether there exists a pair $a \in A$ and $b \in B$ such that $a \cap b = \emptyset$.…

Data Structures and Algorithms · Computer Science 2025-07-16 Anita Dürr , Evangelos Kipouridis , Karol Węgrzycki

The subset sum problem (SSP) can be briefly stated as: given a target integer $E$ and a set $A$ containing $n$ positive integer $a_j$, find a subset of $A$ summing to $E$. The \textit{density} $d$ of an SSP instance is defined by the ratio…

Data Structures and Algorithms · Computer Science 2008-06-23 Changlin Wan , Zhongzhi Shi

In this paper, we study matrix scaling and balancing, which are fundamental problems in scientific computing, with a long line of work on them that dates back to the 1960s. We provide algorithms for both these problems that, ignoring…

Data Structures and Algorithms · Computer Science 2017-08-22 Michael B. Cohen , Aleksander Madry , Dimitris Tsipras , Adrian Vladu

Given $x \in (\mathbb{R}_{\geq 0})^{\binom{[n]}{2}}$ recording pairwise distances, the METRIC VIOLATION DISTANCE (MVD) problem asks to compute the $\ell_0$ distance between $x$ and the metric cone; i.e., modify the minimum number of entries…

Data Structures and Algorithms · Computer Science 2022-08-31 Vincent Cohen-Addad , Chenglin Fan , Euiwoong Lee , Arnaud de Mesmay

Given a multiset $S$ of $n$ positive integers and a target integer $t$, the subset sum problem is to decide if there is a subset of $S$ that sums up to $t$. We present a new divide-and-conquer algorithm that computes all the realizable…

Data Structures and Algorithms · Computer Science 2016-12-13 Konstantinos Koiliaris , Chao Xu

We study the algorithmic problem of estimating the mean of heavy-tailed random vector in $\mathbb{R}^d$, given $n$ i.i.d. samples. The goal is to design an efficient estimator that attains the optimal sub-gaussian error bound, only assuming…

Statistics Theory · Mathematics 2020-02-19 Zhixian Lei , Kyle Luh , Prayaag Venkat , Fred Zhang

We investigate pseudopolynomial-time algorithms for Bounded Knapsack and Bounded Subset Sum. Recent years have seen a growing interest in settling their fine-grained complexity with respect to various parameters. For Bounded Knapsack, the…

Data Structures and Algorithms · Computer Science 2023-12-06 Lin Chen , Jiayi Lian , Yuchen Mao , Guochuan Zhang