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The minimum height of vertex and edge partition trees are well-studied graph parameters known as, for instance, vertex and edge ranking number. While they are NP-hard to determine in general, linear-time algorithms exist for trees.…

Data Structures and Algorithms · Computer Science 2021-05-26 Svein Høgemo , Benjamin Bergougnoux , Ulrik Brandes , Christophe Paul , Jan Arne Telle

Tuning parameters are parameters involved in an estimating procedure for the purpose of reducing the risk of some other estimator. Examples include the degree of penalization in penalized regression and likelihood problems, as well as the…

Statistics Theory · Mathematics 2026-03-31 Ingrid Dæhlen , Nils Lid Hjort , Ingrid Hobæk Haff

We describe a set of $\Delta -1$ slopes that are universal for 1-bend planar drawings of planar graphs of maximum degree $\Delta \geq 4$; this establishes a new upper bound of $\Delta-1$ on the 1-bend planar slope number. By universal we…

Computational Geometry · Computer Science 2017-03-14 Patrizio Angelini , Michael A. Bekos , Giuseppe Liotta , Fabrizio Montecchiani

The planar Tur\'an number of a graph $H$, denoted by $ex_{_\mathcal{P}}(n,H)$, is the largest number of edges in a planar graph on $n $ vertices without containing $H$ as a subgraph. In this paper, we continue to study the topic of…

Combinatorics · Mathematics 2022-09-07 Yongxin Lan , Zi-Xia Song

We study the NP-complete Maximum Outerplanar Subgraph problem. The previous best known approximation ratio for this problem is 2/3. We propose a new approximation algorithm which improves the ratio to 7/10.

Data Structures and Algorithms · Computer Science 2023-06-16 Gruia Calinescu , Hemanshu Kaul , Bahareh Kudarzi

We prove that if an $n$-vertex graph $G$ is non-extremal and $T$ is a bounded degree tree on $n$ vertices, then $T\subset G$ even when the minimum degree of $G$ is less than $n/2$ by a linear term. We avoid the use of the Regularity lemma,…

Combinatorics · Mathematics 2026-05-29 Béla Csaba

In this paper we present a first-order method that admits near-optimal convergence rates for convex/concave min-max problems while requiring a simple and intuitive analysis. Similarly to the seminal work of Nemirovski and the recent…

Computer Science and Game Theory · Computer Science 2023-01-18 Volkan Cevher , Georgios Piliouras , Ryann Sim , Stratis Skoulakis

We consider single-source shortest path algorithms that perform a sequence of relaxation steps whose ordering depends only on the input graph structure and not on its weights or the results of prior steps. Each step examines one edge of the…

Data Structures and Algorithms · Computer Science 2023-05-17 David Eppstein

A regularization algorithm (AR1pGN) for unconstrained nonlinear minimization is considered, which uses a model consisting of a Taylor expansion of arbitrary degree and regularization term involving a possibly non-smooth norm. It is shown…

Optimization and Control · Mathematics 2021-05-31 Serge Gratton , Philippe L. Toint

We settle a problem of Dujmovi\'c, Eppstein, Suderman, and Wood by showing that there exists a function $f$ with the property that every planar graph $G$ with maximum degree $d$ admits a drawing with noncrossing straight-line edges, using…

Combinatorics · Mathematics 2010-11-13 Balázs Keszegh , János Pach , Dömötör Pálvölgyi

For positive integers $n$ and $r$, we consider $n$-vertex graphs with the maximum number of $r$-edge-colorings with no copy of a triangle where exactly two colors appear. We prove that, if $2 \leq r \leq 26$ and $n$ is sufficiently large,…

Combinatorics · Mathematics 2022-09-16 Carlos Hoppen , Hanno Lefmann , Dionatan Ricardo Schmidt

The proximal gradient algorithm for minimizing the sum of a smooth and a nonsmooth convex function often converges linearly even without strong convexity. One common reason is that a multiple of the step length at each iteration may…

Optimization and Control · Mathematics 2016-06-29 Dmitriy Drusvyatskiy , Adrian S. Lewis

We give a new lower bound on the expansion coefficient of an edge-vertex graph of a $d$-regular graph. As a consequence, we obtain an improvement on the lower bound on relative minimum distance of the expander codes constructed by Sipser…

Information Theory · Computer Science 2007-07-13 H. L. Janwa A. K. Lal

Extremal optimization is a new general-purpose method for approximating solutions to hard optimization problems. We study the method in detail by way of the NP-hard graph partitioning problem. We discuss the scaling behavior of extremal…

Statistical Mechanics · Physics 2009-11-07 S. Boettcher , A. G. Percus

We establish the optimal nonergodic sublinear convergence rate of the proximal point algorithm for maximal monotone inclusion problems. First, the optimal bound is formulated by the performance estimation framework, resulting in an infinite…

Optimization and Control · Mathematics 2019-07-15 Guoyong Gu , Junfeng Yang

The crossing resolution of a non-planar drawing of a graph is the value of the minimum angle formed by any pair of crossing edges. Recent experiments have shown that the larger the crossing resolution is, the easier it is to read and…

Data Structures and Algorithms · Computer Science 2018-09-03 Michael A. Bekos , Henry Förster , Christian Geckeler , Lukas Holländer , Michael Kaufmann , Amadäus M. Spallek , Jan Splett

In the Steiner point removal (SPR) problem, we are given a (weighted) graph $G$ and a subset $T$ of its vertices called terminals, and the goal is to compute a (weighted) graph $H$ on $T$ that is a minor of $G$, such that the distance…

Data Structures and Algorithms · Computer Science 2023-10-13 Yu Chen , Zihan Tan

Termination analyses investigate the termination behavior of programs, intending to detect nontermination, which is known to cause a variety of program bugs (e.g. hanging programs, denial-of-service vulnerabilities). Beyond formal…

Software Engineering · Computer Science 2022-08-01 Yoav Alon , Cristina David

We study algorithms for online linear optimization in Hilbert spaces, focusing on the case where the player is unconstrained. We develop a novel characterization of a large class of minimax algorithms, recovering, and even improving,…

Machine Learning · Computer Science 2014-05-22 H. Brendan McMahan , Francesco Orabona

We design and analyze minimax-optimal algorithms for online linear optimization games where the player's choice is unconstrained. The player strives to minimize regret, the difference between his loss and the loss of a post-hoc benchmark…

Machine Learning · Computer Science 2013-02-12 H. Brendan McMahan
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