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Deepak Rajendraprasad
Researcher at Indian Institutes of Technology
Publications - 72
Citations - 566
Deepak Rajendraprasad is an academic researcher from Indian Institutes of Technology. The author has contributed to research in topics: Chordal graph & Dimension (graph theory). The author has an hindex of 13, co-authored 67 publications receiving 513 citations. Previous affiliations of Deepak Rajendraprasad include University of Haifa & Indian Institute of Science.
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An Improvement to Chv\'atal and Thomassen's Upper Bound for Oriented Diameter
TL;DR: In this paper, the authors improved the upper bound to $ 1.373 d^2 + 6.971d-1, which is the best known upper bound for the family of graphs with diameter greater than or equal to 8.
Book ChapterDOI
On Graphs with Minimal Eternal Vertex Cover Number
Jasine Babu,L. Sunil Chandran,Mathew C. Francis,Veena Prabhakaran,Deepak Rajendraprasad,J. Nandini Warrier +5 more
TL;DR: In this article, a polynomial time algorithm for the eternal vertex cover problem was given for a class of graphs that includes chordal graphs and internally triangulated planar graphs.
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Separation dimension and sparsity
TL;DR: In this article, the influence of separation dimension and edge density of a graph on one another was discussed, and it was shown that the maximum separation dimension of a k-degenerate graph on n vertices is O(k lg lgn) and that there exists a family of 2-degree graphs with separation dimension Ω (lg lg n).
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The Induced Separation Dimension of a Graph
TL;DR: This article gives characterizations for chordal graphs in ISD(1) which immediately lead to a polynomial time algorithm which determines the induced separation dimension of chordalGraphs, and shows that the recognition problem for ISD (1) is NP-complete for general graphs.
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Pairwise Suitable Family of Permutations and Boxicity
TL;DR: In this article, the separation dimension of a hypergraph H is equal to the boxicity of the line graph of H. This connection helps us in borrowing results and techniques from the extensive literature on boxicity to study the concept of separation dimension.