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K. Natarajan

12 papers hereh-index 232k citations67 works total

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

author position
  • first author1
  • middle author2
  • last author9

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • math.OC6
  • cs.CG1
  • cs.SI1
  • math.PR1
  • math.ST1
  • q-fin.RM1
same name
  • K. Natarajan — 1 paper, h 2
  • K. Natarajan — 1 paper, h 25
  • K. Natarajan — 1 paper, h 3
  • K. Natarajan — 1 paper, h 1

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
20172025
most citedOptimization of a Triangular Delaunay Mesh Generator using Reinforcement Learning

2 citations · 3 across the 8 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

math.PR2022

Probability bounds for n random events under (n−1)-wise independence

Karthik Natarajan, Arjun Kodagehalli Ramachandra, Colin Tan

A collection of n random events is said to be (n−1)-wise independent if any n−1 events among them are mutually independent. We characterise all probability measures with…

math.OC2022

Pairwise independent correlation gap

Arjun Ramachandra, Karthik Natarajan

In this paper, we introduce the notion of a ``pairwise independent correlation gap'' for set functions with random elements. The pairwise independent correlation gap is defined as…

stat.ML2022

A Nonparametric Approach with Marginals for Modeling Consumer Choice

Yanqiu Ruan, Xiaobo Li, Karthyek Murthy +1

Given data on the choices made by consumers for different offer sets, a key challenge is to develop parsimonious models that describe and predict consumer choice behavior while bei…

math.OC2022

Discrete Optimal Transport with Independent Marginals is #P-Hard

Bahar Taşkesen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn +1

We study the computational complexity of the optimal transport problem that evaluates the Wasserstein distance between the distributions of two K-dimensional discrete random vector…

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