Results 31 to 40 of about 123,539 (262)
Superpatterns and Universal Point Sets [PDF]
, 2013 An old open problem in graph drawing asks for the size of a universal point set, a set of points that can be used as vertices for straight-line drawings of all n-vertex planar graphs.
A. Marcus +14 more
core +3 more sources
Cubic Augmentation of Planar Graphs
, 2012 In this paper we study the problem of augmenting a planar graph such that it becomes 3-regular and remains planar. We show that it is NP-hard to decide whether such an augmentation exists. On the other hand, we give an efficient algorithm for the variant
C.D. Tóth +8 more
core +1 more source
On Partitioning the Edges of 1-Plane Graphs
, 2016 A 1-plane graph is a graph embedded in the plane such that each edge is crossed at most once. A 1-plane graph is optimal if it has maximum edge density.
Lenhart, William J. +2 more
core +1 more source
Non-Uniform Robust Network Design in Planar Graphs [PDF]
, 2015 Robust optimization is concerned with constructing solutions that remain feasible also when a limited number of resources is removed from the solution. Most studies of robust combinatorial optimization to date made the assumption that every resource is ...
Adjiashvili, David
core +2 more sources
OFIDA: Object-focused image data augmentation with attention-driven graph convolutional networks.
PLoS ONEImage data augmentation plays a crucial role in data augmentation (DA) by increasing the quantity and diversity of labeled training data. However, existing methods have limitations.
Meng Zhang +3 more
doaj +1 more source
Minimizing Flow Time in the Wireless Gathering Problem [PDF]
, 2008 We address the problem of efficient data gathering in a wireless network through multi-hop communication. We focus on the objective of minimizing the maximum flow time of a data packet. We prove that no polynomial time algorithm for this problem can have
Alberto Marchetti-Spaccamela +7 more
core +11 more sources
Learning Graph Augmentations to Learn Graph Representations
, 2022 Devising augmentations for graph contrastive learning is challenging due to their irregular structure, drastic distribution shifts, and nonequivalent feature spaces across datasets. We introduce LG2AR, Learning Graph Augmentations to Learn Graph Representations, which is an end-to-end automatic graph augmentation framework that helps encoders learn ...
Hassani, Kaveh, Khasahmadi, Amir Hosein
openaire +2 more sources
MathematicsGraph neural networks (GNNs) are effective for structured data analysis but face reduced learning accuracy due to noisy connections and the necessity for explicit graph structures and labels.
Dongdong An +4 more
doaj +1 more source
Connectivity Augmentation of Graphs
Electronic Notes in Discrete Mathematics, 2000 Abstract We consider the general problem of determining a smallest set of edges which must be added to a given graph (hyper graph, digraph)in order to make it k-edge-connected (k-vertex-connected). We give a short summary of those cases of the augmentation problems which have been solved by polynomial algorithms and min-max formulae. We then describe
Bill Jackson, Tibor Jordánn
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Flow-augmentation II: Undirected Graphs
ACM Transactions on AlgorithmsWe present an undirected version of the recently introduced flow-augmentation technique: Given an undirected multigraph G with distinguished vertices s,t ∈ V(G) and an integer k , one can in randomized k 𝒪(1) ⋅
Eun Jung Kim +3 more
openaire +3 more sources