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We present novel randomized approximation schemes for the Edit Distance (ED) problem and the Longest Common Subsequence (LCS) problem that, for any constant $\epsilon>0$, compute a $(1+\epsilon)$-approximation for ED and a…

Data Structures and Algorithms · Computer Science 2026-04-01 Xiao Mao , Aviad Rubinstein

Given a multiset $X=\{x_1,..., x_n\}$ of real numbers, the {\it floating-point set summation} problem asks for $S_n=x_1+...+x_n$. Let $E^*_n$ denote the minimum worst-case error over all possible orderings of evaluating $S_n$. We prove that…

Data Structures and Algorithms · Computer Science 2024-09-21 Ming-Yang Kao , Jie Wang

We propose a new algorithm to the problem of polygonal curve approximation based on a multiresolution approach. This algorithm is suboptimal but still maintains some optimality between successive levels of resolution using dynamic…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-François Marteau , Gilbas Ménier

In this paper we introduce a dynamic programming algorithm to perform linear text segmentation by global minimization of a segmentation cost function which consists of: (a) within-segment word similarity and (b) prior information about…

Computation and Language · Computer Science 2007-05-23 Pavlina Fragkou

We present semi-streaming algorithms for basic graph problems that have optimal per-edge processing times and therefore surpass all previous semi-streaming algorithms for these tasks. The semi-streaming model, which is appropriate when…

Discrete Mathematics · Computer Science 2007-09-03 Mariano Zelke

The max-cut problem is a classical graph theory problem which is NP-complete. The best polynomial time approximation scheme relies on \emph{semidefinite programming} (SDP). We study the conditions under which graphs of certain classes have…

Optimization and Control · Mathematics 2021-09-07 Daniel Hong , Hyunwoo Lee , Alex Wei

Gradient-based algorithms, popular strategies to optimization problems, are essential for many modern machine-learning techniques. Theoretically, extreme points of certain cost functions can be found iteratively along the directions of the…

Quantum Physics · Physics 2021-04-07 Keren Li , Pan Gao , Shijie Wei , Jiancun Gao , Guilu Long

We investigate the approximation for computing the sum $a_1+...+a_n$ with an input of a list of nonnegative elements $a_1,..., a_n$. If all elements are in the range $[0,1]$, there is a randomized algorithm that can compute an…

Data Structures and Algorithms · Computer Science 2012-03-01 Bin Fu , Wenfeng Li , Zhiyong Peng

Maximizing a monotone submodular function under cardinality constraint $k$ is a core problem in machine learning and database with many basic applications, including video and data summarization, recommendation systems, feature extraction,…

Data Structures and Algorithms · Computer Science 2023-05-25 Kiarash Banihashem , Leyla Biabani , Samira Goudarzi , MohammadTaghi Hajiaghayi , Peyman Jabbarzade , Morteza Monemizadeh

We study the early work scheduling problem on identical parallel machines in order to maximize the total early work, i.e., the parts of non-preemptive jobs executed before a common due date. By preprocessing and constructing an auxiliary…

Data Structures and Algorithms · Computer Science 2020-07-27 Weidong Li

The distinct elements problem is one of the fundamental problems in streaming algorithms --- given a stream of integers in the range $\{1,\ldots,n\}$, we wish to provide a $(1+\varepsilon)$ approximation to the number of distinct elements…

Data Structures and Algorithms · Computer Science 2019-01-07 Jarosław Błasiok

We initiate a systematic study of utilizing predictions to improve over approximation guarantees of classic algorithms, without increasing the running time. We propose a systematic method for a wide class of optimization problems that ask…

Data Structures and Algorithms · Computer Science 2024-11-26 Antonios Antoniadis , Marek Eliáš , Adam Polak , Moritz Venzin

We present the first near optimal approximation schemes for the maximum weighted (uncapacitated or capacitated) $b$--matching problems for non-bipartite graphs that run in time (near) linear in the number of edges. For any…

Data Structures and Algorithms · Computer Science 2018-06-19 Kook Jin Ahn , Sudipto Guha

Many NP-hard problems, such as Dominating Set, are FPT parameterized by clique-width. For graphs of clique-width $k$ given with a $k$-expression, Dominating Set can be solved in $4^k n^{O(1)}$ time. However, no FPT algorithm is known for…

Discrete Mathematics · Computer Science 2015-01-05 Sang-il Oum , Sigve Hortemo Sæther , Martin Vatshelle

A modified dynamic programming algorithm rapidly and accurately solves large 0/1 knapsack problems. It has computational O(nlogn), space O(nlogn) and predictable maximum error. Experimentally it's accuracy increases faster than linearly…

Data Structures and Algorithms · Computer Science 2025-12-30 Nick Dawes

This paper studies the problem of enumerating all maximal collinear subsets of size at least three in a given set of $n$ points. An algorithm for this problem, besides solving degeneracy testing and the exact fitting problem, can also help…

Computational Geometry · Computer Science 2017-06-20 Ali Gholami Rudi , Raimi Ayinde Rufai

We consider the popular $k$-means problem in $d$-dimensional Euclidean space. Recently Friggstad, Rezapour, Salavatipour [FOCS'16] and Cohen-Addad, Klein, Mathieu [FOCS'16] showed that the standard local search algorithm yields a…

Data Structures and Algorithms · Computer Science 2017-08-30 Vincent Cohen-Addad

The library \emph{fast\_polynomial} for Sage compiles multivariate polynomials for subsequent fast evaluation. Several evaluation schemes are handled, such as H\"orner, divide and conquer and new ones can be added easily. Notably, a new…

Symbolic Computation · Computer Science 2013-07-29 Guillaume Moroz

We study the densest subgraph problem and its NP-hard densest at-most-$k$ subgraph variant through the lens of learning-augmented algorithms. We show that, given a reasonably accurate predictor that estimates whether a node belongs to the…

Data Structures and Algorithms · Computer Science 2026-04-16 Thai Bui , Luan Nguyen , Hoa T. Vu

The $k$-segmentation of a video stream is used to partition it into $k$ piecewise-linear segments, so that each linear segment has a meaningful interpretation. Such segmentation may be used to summarize large videos using a small set of…

Computer Vision and Pattern Recognition · Computer Science 2020-09-14 Sabarish Vadarevu , Vijay Karamcheti