Reyan Ahmed
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View article: Word2VecGD: Neural Graph Drawing with Cosine-Stress Optimization
Word2VecGD: Neural Graph Drawing with Cosine-Stress Optimization Open
We propose a novel graph visualization method leveraging random walk-based embeddings to replace costly graph-theoretical distance computations. Using word2vec-inspired embeddings, our approach captures both structural and semantic relatio…
View article: Phytochemical and nutritional variation of country beans (Lablab purpureus) involving parents and hybrids
Phytochemical and nutritional variation of country beans (Lablab purpureus) involving parents and hybrids Open
The fifteen country bean genotypes (Lablab purpureus) were grown to assess the nutritional status and phytochemical analysis. Morphological variation among the genotypes was also evaluated. The experiments were set up using one-way randomi…
View article: Size Should not Matter: Scale-invariant Stress Metrics
Size Should not Matter: Scale-invariant Stress Metrics Open
The normalized stress metric measures how closely distances between vertices in a graph drawing match the graph-theoretic distances between those vertices. It is one of the most widely employed quality metrics for graph drawing, and is eve…
View article: Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search
Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search Open
Graph neural networks have been successful for machine learning, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem. We describe an approach for computing graph spars…
View article: A Scalable Method for Readable Tree Layouts
A Scalable Method for Readable Tree Layouts Open
Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or distances) that need to be communicated to the viewers. Yet…
View article: Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search
Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search Open
Graph neural networks are useful for learning problems, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem. We describe an approach for computing Steiner Trees by com…
View article: Multi-Priority Graph Sparsification
Multi-Priority Graph Sparsification Open
A \emph{sparsification} of a given graph $G$ is a sparser graph (typically a subgraph) which aims to approximate or preserve some property of $G$. Examples of sparsifications include but are not limited to spanning trees, Steiner trees, sp…
View article: Splitting Vertices in 2-Layer Graph Drawings
Splitting Vertices in 2-Layer Graph Drawings Open
Bipartite graphs model the relationships between two disjoint sets of entities in several applications and are naturally drawn as 2-layer graph drawings. In such drawings, the two sets of entities (vertices) are placed on two parallel line…
View article: An FPT Algorithm for Bipartite Vertex Splitting
An FPT Algorithm for Bipartite Vertex Splitting Open
Bipartite graphs model the relationship between two disjoint sets of objects. They have a wide range of applications and are often visualized as a 2-layered drawing, where each set of objects is visualized as a set of vertices (points) on …
View article: Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent,\n $(SGD)^2$
Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent,\n $(SGD)^2$ Open
Readability criteria, such as distance or neighborhood preservation, are\noften used to optimize node-link representations of graphs to enable the\ncomprehension of the underlying data. With few exceptions, graph drawing\nalgorithms typica…
View article: Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent, $(SGD)^2$
Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent, $(SGD)^2$ Open
Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically…
View article: Computing Steiner Trees using Graph Neural Networks
Computing Steiner Trees using Graph Neural Networks Open
Graph neural networks have been successful in many learning problems and real-world applications. A recent line of research explores the power of graph neural networks to solve combinatorial and graph algorithmic problems such as subgraph …
View article: Visualizing Evolving Trees
Visualizing Evolving Trees Open
Evolving trees arise in many real-life scenarios from computer file systems and dynamic call graphs, to fake news propagation and disease spread. Most layout algorithms for static trees do not work well in an evolving setting (e.g., they a…
View article: Multi-level weighted additive spanners
Multi-level weighted additive spanners Open
Given a graph G = (V,E), a subgraph H is an additive +β spanner if dist_H(u,v) ≤ dist_G(u,v) + β for all u, v ∈ V. A pairwise spanner is a spanner for which the above inequality is only required to hold for specific pairs P ⊆ V × V given o…
View article: Weighted Sparse and Lightweight Spanners with Local Additive Error.
Weighted Sparse and Lightweight Spanners with Local Additive Error. Open
An \emph{additive $+\beta$ spanner} of a graph $G$ is a subgraph which preserves shortest paths up to an additive $+\beta$ error. Additive spanners are well-studied in unweighted graphs but have only recently received attention in weighted…
View article: Multi-Level Weighted Additive Spanners
Multi-Level Weighted Additive Spanners Open
Given a graph G = (V,E), a subgraph H is an additive +β spanner if dist_H(u,v) ≤ dist_G(u,v) + β for all u, v ∈ V. A pairwise spanner is a spanner for which the above inequality is only required to hold for specific pairs P ⊆ V × V given o…
View article: On Additive Spanners in Weighted Graphs with Local Error
On Additive Spanners in Weighted Graphs with Local Error Open
View article: New Results and Bounds on Online Facility Assignment Problem
New Results and Bounds on Online Facility Assignment Problem Open
Consider an online facility assignment problem where a set of facilities $F = \{ f_1, f_2, f_3, \cdots, f_{|F|} \}$ of equal capacity $l$ is situated on a metric space and customers arrive one by one in an online manner on that space. We a…
View article: New Results and Bounds on Online Facility Assignment Problem.
New Results and Bounds on Online Facility Assignment Problem. Open
Consider an online facility assignment problem where a set of facilities $F = \{ f_1, f_2, f_3, \cdots, f_{|F|} \}$ of equal capacity $l$ is situated on a metric space and customers arrive one by one in an online manner on that space. We a…
View article: Graph Drawing via Gradient Descent, $(GD)^2$
Graph Drawing via Gradient Descent, $(GD)^2$ Open
Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically…
View article: Graph spanners: A tutorial review
Graph spanners: A tutorial review Open
View article: Kruskal-based approximation algorithm for the multi-level Steiner tree problem
Kruskal-based approximation algorithm for the multi-level Steiner tree problem Open
We study the multi-level Steiner tree problem: a generalization of the Steiner tree problem in graphs where terminals $T$ require varying priority, level, or quality of service. In this problem, we seek to find a minimum cost tree containi…
View article: Weighted Additive Spanners
Weighted Additive Spanners Open
View article: Kruskal-Based Approximation Algorithm for the Multi-Level Steiner Tree Problem
Kruskal-Based Approximation Algorithm for the Multi-Level Steiner Tree Problem Open
We study the multi-level Steiner tree problem: a generalization of the Steiner tree problem in graphs where terminals T require varying priority, level, or quality of service. In this problem, we seek to find a minimum cost tree containing…
View article: Multi-level Steiner Trees
Multi-level Steiner Trees Open
In the classical Steiner tree problem, given an undirected, connected graph G =( V , E ) with non-negative edge costs and a set of terminals T ⊆ V , the objective is to find a minimum-cost tree E &prime ⊆ E that spans the terminals. The pr…
View article: Multi-Level Graph Sketches via Single-Level Solvers
Multi-Level Graph Sketches via Single-Level Solvers Open
Given an undirected weighted graph $G(V,E)$, a constrained sketch over a terminal set $T\subset V$ is a subgraph $G'$ that connects the terminal vertices while satisfying a given set of constraints. Examples include Steiner trees (preservi…
View article: A general framework for multi-level subsetwise graph sparsifiers
A general framework for multi-level subsetwise graph sparsifiers Open
Given an undirected weighted graph $G(V,E)$, a subsetwise sparsifier over a terminal set $T\subset V$ is a subgraph $G'$ having a certain structure which connects the terminals. Examples are Steiner trees (minimal-weight trees spanning $T$…
View article: Approximation algorithms and an integer program for multi-level graph\n spanners
Approximation algorithms and an integer program for multi-level graph\n spanners Open
Given a weighted graph $G(V,E)$ and $t \\ge 1$, a subgraph $H$ is a\n\\emph{$t$--spanner} of $G$ if the lengths of shortest paths in $G$ are\npreserved in $H$ up to a multiplicative factor of $t$. The \\emph{subsetwise\nspanner} problem ai…
View article: Approximation Algorithms and an Integer Program for Multi-level Graph Spanners
Approximation Algorithms and an Integer Program for Multi-level Graph Spanners Open
View article: Stress-Plus-X (SPX) Graph Layout
Stress-Plus-X (SPX) Graph Layout Open