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N. Narayanaswamy

29 papers hereh-index 14910 citations112 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author8
  • middle author9
  • last author11

Across the 28 of 29 papers where every author was matched, so the position is known.

fields
  • cs.DS19
  • cs.DM4
  • cs.CC3
  • math.CO2
  • cs.FL1
same name
  • N. Narayanaswamy — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092023
most citedFaster Parameterized Algorithms using Linear Programming

19 citations · 31 across the 26 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.DS2021

Succinct Data Structure for Path Graphs

Girish Balakrishnan, Sankardeep Chakraborty, N S Narayanaswamy +1

We consider the problem of designing a succinct data structure for {\it path graphs} (which are a proper subclass of chordal graphs and a proper superclass of interval graphs) on $…

cs.DS2021

Parameterized Complexity of Minimum Membership Dominating Set

Akanksha Agrawal, Pratibha Choudhary, N. S. Narayanaswamy +2

Given a graph G=(V,E) and an integer k, the Minimum Membership Dominating Set (MMDS) problem seeks to find a dominating set S⊆V of G such that for each v∈V,…

cs.DS2021★ 1 cited

Parameterized Algorithms for the Steiner Arborescence Problem on a Hypercube

Sugyani Mahapatra, Manikandan Narayanan, N S Narayanaswamy

Motivated by a phylogeny reconstruction problem in evolutionary biology, we study the minimum Steiner arborescence problem on directed hypercubes (MSA-DH). Given m, representing…

cs.DS2021

Budgeted Dominating Sets in Uncertain Graphs

Keerti Choudhary, Avi Cohen, N. S. Narayanaswamy +2

We study the {\em Budgeted Dominating Set} (BDS) problem on uncertain graphs, namely, graphs with a probability distribution p associated with the edges, such that an edge e ex…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.