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We show a flow-augmentation algorithm in directed graphs: There exists a randomized polynomial-time algorithm that, given a directed graph $G$, two vertices $s,t \in V(G)$, and an integer $k$, adds (randomly) to $G$ a number of arcs such…

Data Structures and Algorithms · Computer Science 2023-02-16 Eun Jung Kim , Stefan Kratsch , Marcin Pilipczuk , Magnus Wahlström

Finding diverse solutions in combinatorial problems recently has received considerable attention (Baste et al. 2020; Fomin et al. 2020; Hanaka et al. 2021). In this paper we study the following type of problems: given an integer $k$, the…

Data Structures and Algorithms · Computer Science 2021-12-16 Tesshu Hanaka , Yasuaki Kobayashi , Kazuhiro Kurita , See Woo Lee , Yota Otachi

Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing Gaussian elimination may turn some zeroes into nonzero values. To maintain the matrix sparse, we would like to minimize the number $k$ of these changes, hence…

Computational Complexity · Computer Science 2016-06-28 Yixin Cao , R. B. Sandeep

A vertex $w$ resolves two vertices $u$ and $v$ in a directed graph $G$ if the distance from $w$ to $u$ is different to the distance from $w$ to $v$. A set of vertices $R$ is a resolving set for a directed graph $G$ if for every pair of…

Computational Complexity · Computer Science 2023-06-16 Yannick Schmitz , Egon Wanke

In this paper, we consider the $\ell_0$ minimization problem whose objective function is the sum of $\ell_0$-norm and convex differentiable function. A variable metric type method which combines the PIHT method and the skill in quasi-newton…

Optimization and Control · Mathematics 2021-08-10 Xue Zhang , Xiaoqun Zhang

A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and…

Machine Learning · Computer Science 2013-09-27 Kiyohito Nagano , Yoshinobu Kawahara

We present a general technique, based on parametric search with some twist, for solving a variety of optimization problems on a set of semi-algebraic geometric objects of constant complexity. The common feature of these problems is that…

Computational Geometry · Computer Science 2022-07-15 Matthew J. Katz , Micha Sharir

Interdiction problems ask about the worst-case impact of a limited change to an underlying optimization problem. They are a natural way to measure the robustness of a system, or to identify its weakest spots. Interdiction problems have been…

Optimization and Control · Mathematics 2015-11-10 Stephen R. Chestnut , Rico Zenklusen

We show that, for a fixed order $\gamma\geq 1$, each local minimizer of a rather general nonsmooth optimization problem in Euclidean spaces is either M-stationary in the classical sense (corresponding to stationarity of order $1$),…

Optimization and Control · Mathematics 2023-02-10 Matúš Benko , Patrick Mehlitz

The degree centrality of a node, defined as the number of nodes adjacent to it, is often used as a measure of importance of a node to the structure of a network. This metric can be extended to paths in a network, where the degree centrality…

Data Structures and Algorithms · Computer Science 2025-12-19 Johnson Phosavanh , Dmytro Matsypura

Fine-grained reductions have established equivalences between many core problems with $\tilde{O}(n^3)$-time algorithms on $n$-node weighted graphs, such as Shortest Cycle, All-Pairs Shortest Paths (APSP), Radius, Replacement Paths, Second…

Data Structures and Algorithms · Computer Science 2020-05-07 Andrea Lincoln , Virginia Vassilevska Williams , Ryan Williams

This paper suggests two novel ideas to develop new proximal variable-metric methods for solving a class of composite convex optimization problems. The first idea is a new parameterization of the optimality condition which allows us to…

Optimization and Control · Mathematics 2018-12-14 Quoc Tran-Dinh , Liang Ling , Kim-Chuan Toh

Given an unweighted graph $G$, the *minimum $r$-dominating set problem* asks for the smallest-cardinality subset $S$ such that every vertex in $G$ is within radius $r$ of some vertex in $S$. While the $r$-dominating set problem on planar…

Data Structures and Algorithms · Computer Science 2026-04-02 Reilly Browne , Hsien-Chih Chang

We consider the Minimum Dominating Set (MDS) problem on the intersection graphs of geometric objects. Even for simple and widely-used geometric objects such as rectangles, no sub-logarithmic approximation is known for the problem and…

Computational Geometry · Computer Science 2018-06-26 Sayan Bandyapadhyay , Anil Maheshwari , Saeed Mehrabi , Subhash Suri

Submodular set-functions have many applications in combinatorial optimization, as they can be minimized and approximately maximized in polynomial time. A key element in many of the algorithms and analyses is the possibility of extending the…

Machine Learning · Computer Science 2016-02-24 Francis Bach

We study two "above guarantee" versions of the classical Longest Path problem on undirected and directed graphs and obtain the following results. In the first variant of Longest Path that we study, called Longest Detour, the task is to…

Data Structures and Algorithms · Computer Science 2022-01-11 Fedor V. Fomin , Petr A. Golovach , William Lochet , Danil Sagunov , Kirill Simonov , Saket Saurabh

In machine learning and big data, the optimization objectives based on set-cover, entropy, diversity, influence, feature selection, etc. are commonly modeled as submodular functions. Submodular (function) maximization is generally NP-hard,…

Data Structures and Algorithms · Computer Science 2022-12-13 Haotian Zhang , Rao Li , Zewei Wu , Guodong Sun

Consider a real line equipped with a (not necessarily intrinsic) distance. We deal with the minimum-weight perfect matching problem for a complete graph whose points are located on the line and whose edges have weights equal to distances…

Optimization and Control · Mathematics 2012-12-03 Julie Delon , Julien Salomon , Andrei Sobolevski

The minimax excess risk optimization (MERO) problem is a new variation of the traditional distributionally robust optimization (DRO) problem, which achieves uniformly low regret across all test distributions under suitable conditions. In…

Optimization and Control · Mathematics 2024-08-23 Zhihao Gu , Zi Xu

We study the NP-hard Shortest Path Most Vital Edges problem arising in the context of analyzing network robustness. For an undirected graph with positive integer edge lengths and two designated vertices $s$ and $t$, the goal is to delete as…

Computational Complexity · Computer Science 2018-04-25 Cristina Bazgan , Till Fluschnik , André Nichterlein , Rolf Niedermeier , Maximilian Stahlberg
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