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We present an accelerated relax-and-round algorithm for concave coverage problems, which generalize the classic maximum coverage problem. Building on the relax-and-round framework of Barman et al. [STACS 2021], we propose two significant…

Data Structures and Algorithms · Computer Science 2026-05-11 Matthew Fahrbach , Mehraneh Liaee , Morteza Zadimoghaddam

Orthogonal group synchronization is the problem of estimating $n$ elements $Z_1, \ldots, Z_n$ from the $r \times r$ orthogonal group given some relative measurements $R_{ij} \approx Z_i^{}Z_j^{-1}$. The least-squares formulation is…

Optimization and Control · Mathematics 2024-04-22 Andrew D. McRae , Nicolas Boumal

We consider the power of local algorithms for approximately solving Max $k$XOR, a generalization of two constraint satisfaction problems previously studied with classical and quantum algorithms (MaxCut and Max E3LIN2). In Max $k$XOR each…

Quantum Physics · Physics 2022-07-13 Kunal Marwaha , Stuart Hadfield

We study the fair k-set selection problem where we aim to select $k$ sets from a given set system such that the (weighted) occurrence times that each element appears in these $k$ selected sets are balanced, i.e., the maximum (weighted)…

Data Structures and Algorithms · Computer Science 2025-05-20 Shi Li , Chenyang Xu , Ruilong Zhang

Given a complete graph $G = (V, E)$ where each edge is labeled $+$ or $-$, the Correlation Clustering problem asks to partition $V$ into clusters to minimize the number of $+$edges between different clusters plus the number of $-$edges…

Data Structures and Algorithms · Computer Science 2023-05-04 Vincent Cohen-Addad , Euiwoong Lee , Alantha Newman

We provide improved upper and lower bounds for the Min-Sum-Radii (MSR) and Min-Sum-Diameters (MSD) clustering problems with a bounded number of clusters $k$. In particular, we propose an exact MSD algorithm with running-time $n^{O(k)}$. We…

Data Structures and Algorithms · Computer Science 2025-02-05 Sandip Banerjee , Yair Bartal , Lee-Ad Gottlieb , Alon Hovav

We present an approximation scheme for minimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. This framework includes well known graph problems such as Minimum…

Data Structures and Algorithms · Computer Science 2013-12-12 Venkatesan Guruswami , Ali Kemal Sinop

We present a new explicit construction for expander graphs with nearly optimal spectral gap. The construction is based on a series of 2-lift operations. Let $G$ be a graph on $n$ vertices. A 2-lift of $G$ is a graph $H$ on $2n$ vertices,…

Combinatorics · Mathematics 2007-05-23 Yonatan Bilu , Nathan Linial

We establish the following strengthening of the celebrated Andr{\'a}sfai--Erd\H{o}s--S\'{o}s theorem: If $G$ is an $n$-vertex $K_{r+1}$-free graph whose minimum degree $\delta(G)$ and maximum degree $\Delta(G)$ satisfy \begin{align*}…

Combinatorics · Mathematics 2025-12-12 Xizhi Liu , Sijie Ren , Jian Wang

Jain's iterative rounding theorem is a well-known result in the area of approximation algorithms and, more broadly, in combinatorial optimization. The theorem asserts that LP relaxations of several problems in network design and…

Data Structures and Algorithms · Computer Science 2025-04-18 Miles Simmons , Ishan Bansal , Joe Cheriyan

We develop faster approximation algorithms for Metric-TSP building on recent, nearly linear time approximation schemes for the LP relaxation [Chekuri and Quanrud, 2017]. We show that the LP solution can be sparsified via cut-sparsification…

Data Structures and Algorithms · Computer Science 2018-02-06 Chandra Chekuri , Kent Quanrud

We prove a general result demonstrating the power of Lagrangian relaxation in solving constrained maximization problems with arbitrary objective functions. This yields a unified approach for solving a wide class of {\em subset selection}…

Data Structures and Algorithms · Computer Science 2015-12-22 Ariel Kulik , Hadas Shachnai , Gal Tamir

We study two problems that seek a subtree $T$ of a graph $G=(V,E)$ such that $T$ satisfies a certain property and has minimal maximum degree. - In the Min-Degree Group Steiner Tree problem we are given a collection ${\cal S}$ of groups…

Data Structures and Algorithms · Computer Science 2019-10-29 Guy Kortsarz , Zeev Nutov

Effective Resistance (ER) is a fundamental tool in various graph learning tasks. In this paper, we address the problem of efficiently approximating ER on a graph $\mathcal{G}=(\mathcal{V},\mathcal{E})$ with $n$ vertices and $m$ edges.…

Data Structures and Algorithms · Computer Science 2025-07-08 Yichun Yang , Rong-Hua Li , Meihao Liao , Guoren Wang

We present a near-optimal polynomial-time approximation algorithm for the asymmetric traveling salesman problem for graphs of bounded orientable or non-orientable genus. Our algorithm achieves an approximation factor of O(f(g)) on graphs…

Data Structures and Algorithms · Computer Science 2013-05-14 Jeff Erickson , Anastasios Sidiropoulos

We approach the Max-3-Cut problem through the lens of maximizing complex-valued quadratic forms and demonstrate that low-rank structure in the objective matrix can be exploited, leading to alternative algorithms to classical semidefinite…

Data Structures and Algorithms · Computer Science 2026-04-27 Ria Stevens , Fangshuo Liao , Barbara Su , Jianqiang Li , Anastasios Kyrillidis

The $r$-expansion of a $k$-uniform hypergraph $H$, denoted by $H^{(+r)}$, is an $r$-uniform hypergraph obtained by enlarging each $k$-edge of $H$ with a set of $r-k$ vertices of degree one. The random Tur\'an number…

Combinatorics · Mathematics 2024-05-21 Jiaxi Nie

Whether or not the Sparsest Cut problem admits an efficient $O(1)$-approximation algorithm is a fundamental algorithmic question with connections to geometry and the Unique Games Conjecture. Revisiting spectral algorithms for Sparsest Cut,…

Data Structures and Algorithms · Computer Science 2025-10-01 Tommaso d'Orsi , Chris Jones , Jake Ruotolo , Salil Vadhan , Jiyu Zhang

The densest k-subgraph (DkS) problem (i.e. find a size k subgraph with maximum number of edges), is one of the notorious problems in approximation algorithms. There is a significant gap between known upper and lower bounds for DkS: the…

Data Structures and Algorithms · Computer Science 2011-10-07 Aditya Bhaskara , Moses Charikar , Venkatesan Guruswami , Aravindan Vijayaraghavan , Yuan Zhou

We prove that any graph excluding $K_r$ as a minor has can be partitioned into clusters of diameter at most $\Delta$ while removing at most $O(r/\Delta)$ fraction of the edges. This improves over the results of Fakcharoenphol and Talwar,…

Data Structures and Algorithms · Computer Science 2021-01-12 Ittai Abraham , Cyril Gavoille , Anupam Gupta , Ofer Neiman , Kunal Talwar