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We consider a recently introduced fair repetitive scheduling problem involving a set of clients, each asking for their associated job to be daily scheduled on a single machine across a finite planning horizon. The goal is to determine a job…

Data Structures and Algorithms · Computer Science 2026-01-01 Danny Hermelin , Danny Segev , Dvir Shabtay

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 present a sorting algorithm for the case of recurrent random comparison errors. The algorithm essentially achieves simultaneously good properties of previous algorithms for sorting $n$ distinct elements in this model. In particular, it…

Data Structures and Algorithms · Computer Science 2017-09-22 Barbara Geissmann , Stefano Leucci , Chih-Hung Liu , Paolo Penna

Longest common extension queries (LCE queries) and runs are ubiquitous in algorithmic stringology. Linear-time algorithms computing runs and preprocessing for constant-time LCE queries have been known for over a decade. However, these…

Data Structures and Algorithms · Computer Science 2016-06-28 Maxime Crochemore , Costas S. Iliopoulos , Tomasz Kociumaka , Ritu Kundu , Solon P. Pissis , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń

We present the first explicit comparison-based algorithm that sorts the sumset $X + Y = \{x_i + y_j,\ \forall 0 \le i, j < n\}$, where $X$ and $Y$ are sorted arrays of real numbers, in optimal $O(n^2)$ time and comparisons. While Fredman…

Data Structures and Algorithms · Computer Science 2025-04-24 S. Mundhra

Given an approximation algorithm $A$, we want to find the input with the worst approximation ratio, i.e., the input for which $A$'s output's objective value is the worst possible compared to the optimal solution's objective value. Such hard…

Data Structures and Algorithms · Computer Science 2025-04-29 Eklavya Sharma

We describe the first nearly linear-time approximation algorithms for explicitly given mixed packing/covering linear programs, and for (non-metric) fractional facility location. We also describe the first parallel algorithms requiring only…

Data Structures and Algorithms · Computer Science 2014-11-06 Neal E. Young

Since the Bin Packing Problem (BPP) is one of the main NP-hard problems, a lot of approximation algorithms have been suggested for it. It has been proven that the best algorithm for BPP has the approximation ratio of 3/2 and the time order…

Discrete Mathematics · Computer Science 2016-10-28 Abdolahad Noori Zehmakan

We present an $O(n\sqrt{\log n})$ time and linear space algorithm for sorting real numbers. This breaks the long time illusion that real numbers have to be sorted by comparison sorting and take $\Omega (n\log n)$ time to be sorted.

Data Structures and Algorithms · Computer Science 2018-12-04 Yijie Han

We investigate the scheduling of $n$ jobs divided into $c$ classes on $m$ identical parallel machines. For every class there is a setup time which is required whenever a machine switches from the processing of one class to another class.…

Data Structures and Algorithms · Computer Science 2019-05-02 Max A. Deppert , Klaus Jansen

We study the $L_2$-approximation of functions from a Hilbert space and compare the sampling numbers with the approximation numbers. The sampling number $e_n$ is the minimal worst case error that can be achieved with $n$ function values,…

Numerical Analysis · Mathematics 2024-10-15 David Krieg , Mario Ullrich

We study the optimization version of the set partition problem (where the difference between the partition sums are minimized), which has numerous applications in decision theory literature. While the set partitioning problem is NP-hard and…

Data Structures and Algorithms · Computer Science 2021-09-13 Kaan Gokcesu , Hakan Gokcesu

Many convex problems in machine learning and computer science share the same form: \begin{align*} \min_{x} \sum_{i} f_i( A_i x + b_i), \end{align*} where $f_i$ are convex functions on $\mathbb{R}^{n_i}$ with constant $n_i$, $A_i \in…

Data Structures and Algorithms · Computer Science 2019-05-14 Yin Tat Lee , Zhao Song , Qiuyi Zhang

We consider computing a longest palindrome in the streaming model, where the symbols arrive one-by-one and we do not have random access to the input. While computing the answer exactly using sublinear space is not possible in such a…

Data Structures and Algorithms · Computer Science 2016-10-12 Paweł Gawrychowski , Oleg Merkurev , Arseny M. Shur , Przemysław Uznański

We study the classical scheduling problem on parallel machines %with precedence constraints where the precedence graph has the bounded depth $h$. Our goal is to minimize the maximum completion time. We focus on developing approximation…

Data Structures and Algorithms · Computer Science 2023-02-02 Bin Fu , Yumei Huo , Hairong Zhao

Given n positive integers, the Modular Subset Sum problem asks if a subset adds up to a given target t modulo a given integer m. This is a natural generalization of the Subset Sum problem (where m=+\infty) with ties to additive…

Data Structures and Algorithms · Computer Science 2018-07-16 Kyriakos Axiotis , Arturs Backurs , Christos Tzamos

In the minimum planarization problem, given some $n$-vertex graph, the goal is to find a set of vertices of minimum cardinality whose removal leaves a planar graph. This is a fundamental problem in topological graph theory. We present a…

Data Structures and Algorithms · Computer Science 2017-08-17 Ken-ichi Kawarabayashi , Anastasios Sidiropoulos

We formalize the problem of selecting the optimal set of options for planning as that of computing the smallest set of options so that planning converges in less than a given maximum of value-iteration passes. We first show that the problem…

Artificial Intelligence · Computer Science 2019-03-19 Yuu Jinnai , David Abel , D Ellis Hershkowitz , Michael Littman , George Konidaris

We consider the classical makespan minimization scheduling problem where $n$ jobs must be scheduled on $m$ identical machines. Using weighted random sampling, we developed two sublinear time approximation schemes: one for the case where $n$…

Data Structures and Algorithms · Computer Science 2026-05-05 Bin Fu , Yumei Huo , Hairong Zhao

We study the problem of estimating the size of a maximum matching in sublinear time. The problem has been studied extensively in the literature and various algorithms and lower bounds are known for it. Our result is a $0.5109$-approximation…

Data Structures and Algorithms · Computer Science 2025-06-03 Sepideh Mahabadi , Mohammad Roghani , Jakub Tarnawski