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In this paper we provide an $O(m (\log \log n)^{O(1)} \log(1/\epsilon))$-expected time algorithm for solving Laplacian systems on $n$-node $m$-edge graphs, improving improving upon the previous best expected runtime of $O(m \sqrt{\log n}…

Data Structures and Algorithms · Computer Science 2023-04-04 Arun Jambulapati , Aaron Sidford

We present a novel self-stabilizing algorithm for minimum spanning tree (MST) construction. The space complexity of our solution is $O(\log^2n)$ bits and it converges in $O(n^2)$ rounds. Thus, this algorithm improves the convergence time of…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-26 Lélia Blin , Shlomi Dolev , Maria Potop-Butucaru , Stephane Rovedakis

We present a new elementary algorithm that takes \[ \mathrm{time} \ \ O_\epsilon\left(x^{\frac{3}{5}} (\log x)^{\frac{3}{5}+\epsilon} \right) \ \ \mathrm{and}\ \ \mathrm{space} \ \ O\left(x^{\frac{3}{10}} (\log x)^{\frac{13}{10}} \right)\]…

Number Theory · Mathematics 2022-03-01 Harald A. Helfgott , Lola Thompson

Permutation patterns and pattern avoidance have been intensively studied in combinatorics and computer science, going back at least to the seminal work of Knuth on stack-sorting (1968). Perhaps the most natural algorithmic question in this…

Data Structures and Algorithms · Computer Science 2019-08-14 Benjamin Aram Berendsohn , László Kozma , Dániel Marx

There has recently been much progress on exact algorithms for the (un)weighted graph (bi)partitioning problem using branch-and-bound and related methods. In this note we present and improve an easily computable, purely combinatorial lower…

Data Structures and Algorithms · Computer Science 2014-10-03 Jesper Larsson Träff , Martin Wimmer

One approach for reducing run time and improving efficiency of machine learning is to reduce the convergence rate of the optimization algorithm used. Shuffling is an algorithm technique that is widely used in machine learning, but it only…

Machine Learning · Computer Science 2023-06-29 Yuetong Xu , Baharan Mirzasoleiman

For two d-dimensional point sets A, B of size up to n, the Chamfer distance from A to B is defined as CH(A,B) = \sum_{a \in A} \min_{b \in B} \|a-b\|. The Chamfer distance is a widely used measure for quantifying dissimilarity between sets…

Computational Geometry · Computer Science 2025-09-04 Ying Feng , Piotr Indyk

We consider the problem of minimizing the total processing time of tardy jobs on a single machine. This is a classical scheduling problem, first considered by [Lawler and Moore 1969], that also generalizes the Subset Sum problem. Recently,…

Data Structures and Algorithms · Computer Science 2023-01-18 Baruch Schieber , Pranav Sitaraman

Pattern matching is a fundamental process in almost every scientific domain. The problem involves finding the positions of a given pattern (usually of short length) in a reference stream of data (usually of large length). The matching can…

Data Structures and Algorithms · Computer Science 2022-07-01 Anas Al-okaily , Abdelghani Tbakhi

A stochastic leap-frog algorithm for the numerical integration of Brownian motion stochastic differential equations with multiplicative noise is proposed and tested. The algorithm has a second-order convergence of moments in a finite time…

Computational Physics · Physics 2009-10-31 Ji Qiang , Salman Habib

The classic algorithm [Papadimitriou, J.ACM '81] for IPs has a running time $n^{O(m)}(m\cdot\max\{\Delta,\|\textbf{b}\|_{\infty}\})^{O(m^2)}$, where $m$ is the number of constraints, $n$ is the number of variables, and $\Delta$ and…

Optimization and Control · Mathematics 2026-01-01 Hauke Brinkop , Hua Chen , Lin Chen , Klaus Jansen , Guochuan Zhang

In a classical scheduling problem, we are given a set of $n$ jobs of unit length along with precedence constraints, and the goal is to find a schedule of these jobs on $m$ identical machines that minimizes the makespan. Using the standard…

Data Structures and Algorithms · Computer Science 2023-12-07 Jesper Nederlof , Céline M. F. Swennenhuis , Karol Węgrzycki

A fundamental problem in shape matching and geometric similarity is computing the maximum area overlap between two polygons under translation. For general simple polygons, the best-known algorithm runs in $O((nm)^2 \log(nm))$ time [Mount,…

Computational Geometry · Computer Science 2025-11-07 Mikkel Abrahamsen , Sujoy Bhore , Maike Buchin , Jacobus Conradi , Ce Jin , André Nusser , Carolin Rehs

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

Given a pattern of length $m$ and a text of length $n$, the goal in $k$-mismatch pattern matching is to compute, for every $m$-substring of the text, the exact Hamming distance to the pattern or report that it exceeds $k$. This can be…

Data Structures and Algorithms · Computer Science 2017-04-06 Paweł Gawrychowski , Przemysław Uznański

Time-dependent scheduling with linear deterioration involves determining when to execute jobs whose processing times degrade as their beginning is delayed. Each job i is associated with a release time r_i and a processing time function…

Data Structures and Algorithms · Computer Science 2023-07-04 Angelos Gkikas , Dimitrios Letsios , Tomasz Radzik , Kathleen Steinhöfel

We give new sublinear and parallel algorithms for the extensively studied problem of approximating n-variable r-CSPs (constraint satisfaction problems with constraints of arity r up to an additive error. The running time of our algorithms…

Data Structures and Algorithms · Computer Science 2014-07-31 Grigory Yaroslavtsev

We present an algorithm for computing a bottleneck matching in a set of $n=2\ell$ points in the plane, which runs in $O(n^{\omega/2}\log n)$ deterministic time, where $\omega\approx 2.37$ is the exponent of matrix multiplication.

Computational Geometry · Computer Science 2022-05-13 Matthew J. Katz , Micha Sharir

We revisit two well-known algorithmic problems on strings: computing a shortest unique substring (SUS) and a shortest absent substring (SAS) of a string $S$ of length $n$. Both problems admit folklore $\mathcal{O}(n)$-time solutions using…

Data Structures and Algorithms · Computer Science 2026-05-07 Panagiotis Charalampopoulos , Manal Mohamed , Solon P. Pissis , Hilde Verbeek , Wiktor Zuba

We consider the problem of preprocessing two strings $S$ and $T$, of lengths $m$ and $n$, respectively, in order to be able to efficiently answer the following queries: Given positions $i,j$ in $S$ and positions $a,b$ in $T$, return the…

Data Structures and Algorithms · Computer Science 2021-03-08 Panagiotis Charalampopoulos , Paweł Gawrychowski , Shay Mozes , Oren Weimann