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Related papers: Greedy Completion for Weighted $(\alpha,\beta)$-Sp…

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We consider base-$\beta$ expansions of Parry's type, where $a_0 \geq a_1 \geq 1$ are integers and $a_0<\beta <a_0+1$ is the positive solution to $\beta^2 = a_0\beta + a_1$ (the golden ratio corresponds to $a_0=a_1=1$). The map $x\mapsto…

Dynamical Systems · Mathematics 2026-05-20 Horia D. Cornean , Kasper S. Sørensen

In this paper we consider the task of estimating the non-zero pattern of the sparse inverse covariance matrix of a zero-mean Gaussian random vector from a set of iid samples. Note that this is also equivalent to recovering the underlying…

Machine Learning · Computer Science 2012-02-28 Christopher C. Johnson , Ali Jalali , Pradeep Ravikumar

We study methods to manipulate weights in stress-graph embeddings to improve convex straight-line planar drawings of 3-connected planar graphs. Stress-graph embeddings are weighted versions of Tutte embeddings, where solving a linear system…

Computational Geometry · Computer Science 2023-09-01 Alvin Chiu , David Eppstein , Michael T. Goodrich

This paper introduces a greedy parser based on neural networks, which leverages a new compositional sub-tree representation. The greedy parser and the compositional procedure are jointly trained, and tightly depends on each-other. The…

Machine Learning · Computer Science 2015-04-14 Joël Legrand , Ronan Collobert

We present a family of numerical implementations of Kato's ODE propagating global bases of analytically varying invariant subspaces, of which the first-order version is a surprising simple "greedy algorithm" that is both stable and easy to…

Numerical Analysis · Mathematics 2008-10-06 Kevin Zumbrun

Recent work has pinned down the existentially optimal size bounds for vertex fault-tolerant spanners: for any positive integer $k$, every $n$-node graph has a $(2k-1)$-spanner on $O(f^{1-1/k} n^{1+1/k})$ edges resilient to $f$ vertex…

Data Structures and Algorithms · Computer Science 2020-11-03 Greg Bodwin , Michael Dinitz , Caleb Robelle

Recently there has been much interest in "sparsifying" sums of rank one matrices: modifying the coefficients such that only a few are nonzero, while approximately preserving the matrix that results from the sum. Results of this sort have…

Discrete Mathematics · Computer Science 2018-01-30 Marcel K. de Carli Silva , Nicholas J. A. Harvey , Cristiane M. Sato

We present a $+2\sum_{i=1}^{k+1}{W_i}$-APASP algorithm for dense weighted graphs with runtime $\tilde O\left(n^{2+\frac{1}{3k+2}}\right)$, where $W_{i}$ is the weight of an $i^{th}$ heaviest edge on a shortest path. Dor, Halperin and Zwick…

Data Structures and Algorithms · Computer Science 2026-02-17 Liam Roditty , Ariel Sapir

We introduce in a general setting a dynamic programming method for solving reconfiguration problems. Our method is based on contracted solution graphs, which are obtained from solution graphs by performing an appropriate series of edge…

Data Structures and Algorithms · Computer Science 2018-07-13 Paul Bonsma , Daniel Paulusma

We study the parameterized complexity of a broad class of problems called "local graph partitioning problems" that includes the classical fixed cardinality problems as max k-vertex cover, k-densest subgraph, etc. By developing a technique…

Computational Complexity · Computer Science 2013-06-11 Edouard Bonnet , Bruno Escoffier , Vangelis Th. Paschos , Emeric Tourniaire

The total effective resistance, also called the Kirchhoff index, provides a robustness measure for a graph $G$. We consider two optimization problems of adding $k$ new edges to $G$ such that the resulting graph has minimal total effective…

Social and Information Networks · Computer Science 2023-09-18 Maria Predari , Lukas Berner , Robert Kooij , Henning Meyerhenke

In this note, we analyze two random greedy processes on sparse random graphs and hypergraphs with a given degree sequence. First we analyze the matching process, which builds a set of disjoint edges one edge at a time; then we analyze the…

Combinatorics · Mathematics 2021-09-24 Deepak Bal , Patrick Bennett

For a positive integer $t$ and a graph $G$, an additive $t$-spanner of $G$ is a spanning subgraph in which the distance between every pair of vertices is at most the original distance plus $t$. Minimum Additive $t$-Spanner Problem is to…

Data Structures and Algorithms · Computer Science 2019-03-05 Yusuke Kobayashi

In the pairwise weighted spanner problem, the input consists of an $n$-vertex-directed graph, where each edge is assigned a cost and a length. Given $k$ vertex pairs and a distance constraint for each pair, the goal is to find a…

Data Structures and Algorithms · Computer Science 2023-07-10 Elena Grigorescu , Nithish Kumar , Young-San Lin

Highly connected and yet sparse graphs (such as expanders or graphs of high treewidth) are fundamental, widely applicable and extensively studied combinatorial objects. We initiate the study of such highly connected graphs that are, in…

Computational Geometry · Computer Science 2013-06-17 Prosenjit Bose , Vida Dujmovic , Pat Morin , Michiel Smid

We study resistance sparsification of graphs, in which the goal is to find a sparse subgraph (with reweighted edges) that approximately preserves the effective resistances between every pair of nodes. We show that every dense regular…

Data Structures and Algorithms · Computer Science 2015-06-26 Michael Dinitz , Robert Krauthgamer , Tal Wagner

In this paper, we address the problem of learning the structure of a pairwise graphical model from samples in a high-dimensional setting. Our first main result studies the sparsistency, or consistency in sparsity pattern recovery,…

Machine Learning · Computer Science 2012-02-28 Ali Jalali , Chris Johnson , Pradeep Ravikumar

Recently, a new way of avoiding crossings in straight-line drawings of non-planar graphs has been investigated. The idea of partial edge drawings (PED) is to drop the middle part of edges and rely on the remaining edge parts called stubs.…

In many prediction problems, it is not uncommon that the number of variables used to construct a forecast is of the same order of magnitude as the sample size, if not larger. We then face the problem of constructing a prediction in the…

Statistics Theory · Mathematics 2016-02-08 Alessio Sancetta

Greedy algorithms are central to sparse approximation and stage-wise learning methods such as matching pursuit and boosting. It is known that the Power-Relaxed Greedy Algorithm with step sizes $m^{-\alpha}$ may fail to converge when…

Machine Learning · Computer Science 2026-03-10 Pablo M. Berná
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