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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

The computational complexity of the partition, 0-1 subset sum, unbounded subset sum, 0-1 knapsack and unbounded knapsack problems and their multiple variants were studied in numerous papers in the past where all the weights and profits were…

Discrete Mathematics · Computer Science 2018-02-27 Dominik Wojtczak

We provide an algorithm for properly learning mixtures of two single-dimensional Gaussians without any separability assumptions. Given $\tilde{O}(1/\varepsilon^2)$ samples from an unknown mixture, our algorithm outputs a mixture that is…

Data Structures and Algorithms · Computer Science 2014-05-20 Constantinos Daskalakis , Gautam Kamath

We propose a fast proximal Newton-type algorithm for minimizing regularized finite sums that returns an $\epsilon$-suboptimal point in $\tilde{\mathcal{O}}(d(n + \sqrt{\kappa d})\log(\frac{1}{\epsilon}))$ FLOPS, where $n$ is number of…

Machine Learning · Computer Science 2017-08-30 Xuanqing Liu , Cho-Jui Hsieh , Jason D. Lee , Yuekai Sun

An important goal in algorithm design is determining the best running time for solving a problem (approximately). For some problems, we know the optimal running time, assuming certain conditional lower bounds. In this work, we study the…

Data Structures and Algorithms · Computer Science 2024-03-04 Moritz Buchem , Paul Deuker , Andreas Wiese

We study the correlated stochastic knapsack problem of a submodular target function, with optional additional constraints. We utilize the multilinear extension of submodular function, and bundle it with an adaptation of the relaxed linear…

Data Structures and Algorithms · Computer Science 2022-08-04 Sheng Yang , Samir Khuller , Sunav Choudhary , Subrata Mitra , Kanak Mahadik

The study of Dense-$3$-Subhypergraph problem was initiated in Chlamt{\'{a}}c et al. [Approx'16]. The input is a universe $U$ and collection ${\cal S}$ of subsets of $U$, each of size $3$, and a number $k$. The goal is to choose a set $W$ of…

Data Structures and Algorithms · Computer Science 2018-01-25 Amey Bhangale , Rajiv Gandhi , Guy Kortsarz

We study the fundamental problem of approximating the edit distance of two strings. After an extensive line of research led to the development of a constant-factor approximation algorithm in almost-linear time, recent years have witnessed a…

Data Structures and Algorithms · Computer Science 2023-12-05 Karl Bringmann , Alejandro Cassis , Nick Fischer , Tomasz Kociumaka

The (unweighted) point-separation problem asks, given a pair of points $s$ and $t$ in the plane, and a set of candidate geometric objects, for the minimum-size subset of objects whose union blocks all paths from $s$ to $t$. Recent work has…

Computational Geometry · Computer Science 2026-02-16 Jayson Lynch , Jack Spalding-Jamieson

The classical work of (Arora et al., 1999) provides a scheme that gives, for any $\epsilon>0$, a polynomial time $1-\epsilon$ approximation algorithm for dense instances of a family of $\mathcal{NP}$-hard problems, such as Max-CUT and…

Data Structures and Algorithms · Computer Science 2024-05-24 Evripidis Bampis , Bruno Escoffier , Michalis Xefteris

We introduce and study a novel generalization of the classical Knapsack Problem (KP), called the Colored Knapsack Problem (CKP). In this problem, the items are partitioned into classes of colors and the packed items need to be ordered such…

Optimization and Control · Mathematics 2026-02-13 Fabio Ciccarelli , Alexander Helber , Erik Mühmer

In this paper, we consider the unconstrained submodular maximization problem. We propose the first algorithm for this problem that achieves a tight $(1/2-\varepsilon)$-approximation guarantee using $\tilde{O}(\varepsilon^{-1})$ adaptive…

Data Structures and Algorithms · Computer Science 2018-11-20 Lin Chen , Moran Feldman , Amin Karbasi

In this paper, we investigate the parametric knapsack problem, in which the item profits are affine functions depending on a real-valued parameter. The aim is to provide a solution for all values of the parameter. It is well-known that any…

Data Structures and Algorithms · Computer Science 2017-01-30 Michael Holzhauser , Sven O. Krumke

The Subset Sum Ratio problem (SSR) asks, given a multiset $A$ of positive integers, to find two disjoint subsets of $A$ such that the largest-to-smallest ratio of their sums is minimized. In this paper we study the $k$-version of SSR,…

The Dyck language, which consists of well-balanced sequences of parentheses, is one of the most fundamental context-free languages. The Dyck edit distance quantifies the number of edits (character insertions, deletions, and substitutions)…

Data Structures and Algorithms · Computer Science 2021-12-14 Debarati Das , Tomasz Kociumaka , Barna Saha

We consider the product knapsack problem, which is the variant of the classical 0-1 knapsack problem where the objective consists of maximizing the product of the profits of the selected items. These profits are allowed to be positive or…

Optimization and Control · Mathematics 2021-06-29 Ulrich Pferschy , Joachim Schauer , Clemens Thielen

We address the classical knapsack problem and a variant in which an upper bound is imposed on the number of items that can be selected. We show that appropriate combinations of rounding techniques yield novel and powerful ways of rounding.…

Computational Complexity · Computer Science 2007-05-23 Monaldo Mastrolilli , Marcus Hutter

Min-plus product of two $n\times n$ matrices is a fundamental problem in algorithm research. It is known to be equivalent to APSP, and in general it has no truly subcubic algorithms. In this paper, we focus on the min-plus product on a…

Data Structures and Algorithms · Computer Science 2022-02-03 Shucheng Chi , Ran Duan , Tianle Xie

In resource allocation, we often require that the output allocation of an algorithm is stable against input perturbation because frequent reallocation is costly and untrustworthy. Varma and Yoshida (SODA'21) formalized this requirement for…

Data Structures and Algorithms · Computer Science 2024-05-24 Soh Kumabe , Yuichi Yoshida

We give a stochastic optimization algorithm that solves a dense $n\times n$ real-valued linear system $Ax=b$, returning $\tilde x$ such that $\|A\tilde x-b\|\leq \epsilon\|b\|$ in time: $$\tilde O((n^2+nk^{\omega-1})\log1/\epsilon),$$ where…

Data Structures and Algorithms · Computer Science 2024-06-10 Michał Dereziński , Jiaming Yang
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