activity
20142026
most citedFirst Passage Percolation with nonidentical passage times

4 citations · 13 across the 58 of their papers we have counts for

collaborators

63 papers

cs.LG2026

Criticality in Dissimilar Decomposition and Undersampling of Random Datasets with Anomalies

Ghurumuruhan Ganesan

Training datasets for upcoming LLMs would include a significant amount of AI text/image data generated from current LLMs. In such a scenario, it is important to understand how this…

math.PR2026

Extremal Spanning Trees of Random Marked Graphs with Independent Edge Weights

Ghurumuruhan Ganesan

In this paper, we consider a Bernoulli random graph~\(G\) on~\(n\) vertices with non-uniform edge probabilities, where each vertex has an independent mark and each edge is equipped…

math.PR2026

Constrained Maximum Weight Paths in Random Geometric Graphs

Ghurumuruhan Ganesan

In this paper, we consider a random geometric graph (RGG)~\(G\) formed by~\(n\) vertices distributed uniformly in the unit square~\(S\) on the plane and equip each edge of~\(G\) wi…

math.PR2026

Maximum Spanning Trees of Random Geometric Graphs With Independent Edge Weights

Ghurumuruhan Ganesan

In this paper, we study maximum weight spanning trees of the random geometric graph (RGG)~\(G\) formed by~\(n\) vertices where each edge is independently either open or closed with…

math.PR2025

Deviation Estimates for Extremal Relay Random Geometric Graphs

Ghurumuruhan Ganesan

In this paper, we consider a deterministic graph~\(Γ\) drawn on the unit square with straight line segments as edges and connect vertices of~\(Γ\) using edges of a random geometric…

math.PR2025

Extremal Planar Matchings of Inhomogenous Random Bipartite Graphs

Ghurumuruhan Ganesan

In this paper we study maximum size and minimum weight planar matchings of inhomogenous random bipartite graphs. Our motivation for this study comes from efficient usage of cross e…

cs.LG2025

Dissimilar Batch Decompositions of Random Datasets

Ghurumuruhan Ganesan

For better learning, large datasets are often split into small batches and fed sequentially to the predictive model. In this paper, we study such batch decompositions from a probab…

math.PR2024

Dirac-type Theorems for Inhomogenous Random Graphs

Ghurumuruhan Ganesan

In this paper, we study Dirac-type theorems for an inhomogenous random graph (G) whose edge probabilities are not necessarily all the same. We obtain sufficient conditions for the…

math.PR2024

Tracking the Mean of a Piecewise Stationary Sequence

Ghurumuruhan Ganesan

In this paper we study the problem of tracking the mean of a piecewise stationary sequence of independent random variables. First we consider the case where the transition times ar…

cs.IT2024

Classification and Regression Error Bounds for Inhomogenous Data With Applications to Wireless Networks

Ghurumuruhan Ganesan

In this paper, we study classification and regression error bounds for inhomogenous data that are independent but not necessarily identically distributed. First, we consider classi…

math.CO2023

Linearity and Local Correctness in Weighted Colourings of Random Graphs

Ghurumuruhan Ganesan

In this paper, we consider a weighted generalization of the chromatic number of a Binomial random graph~\(G.\) We equip each edge with a random weight and then colour the vertices…

math.CO2023★ 1 cited

Linearity Property of Unique Colourings in Random Graphs

Ghurumuruhan Ganesan

In this paper, we study unique colourings in random graphs as a generalization of both conflict-free and injective colourings. Specifically, we impose the condition that a fraction…

math.PR2023★ 1 cited

Critical Exponent for the Acyclic Chromatic Number of Random Graphs

Ghurumuruhan Ganesan

In this paper we study acyclic colouring in the random subgraph of the complete graph on vertices where each edge is present with probabili…

cs.LG2023

A Probabilistic Model for Data Redundancy in the Feature Domain

Ghurumuruhan Ganesan

In this paper, we use a probabilistic model to estimate the number of uncorrelated features in a large dataset. Our model allows for both pairwise feature correlation (collinearity…

cs.IT2023★ 1 cited

Probabilistic Bounds for Data Storage with Feature Selection and Undersampling

Ghurumuruhan Ganesan

In this paper we consider data storage from a probabilistic point of view and obtain bounds for efficient storage in the presence of feature selection and undersampling, both of wh…

cs.IT2023

Linear Codes with Prescribed Hull Dimension and Minimum Distance

Ghurumuruhan Ganesan

The hull of a linear code (i.e., a finite field vector space)~\({\mathcal C}\) is defined to be the vector space formed by the intersection of~\({\mathcal C}\) with its dual~\({\ma…

math.PR2023★ 1 cited

Linear Eulerian Extensions of Inhomogenous Random Graphs

Ghurumuruhan Ganesan

The Eulerian extension number of any graph~\(H\) (i.e. the minimum number of edges needed to be added to make~\(H\) Eulerian) is at least~\(t(H),\) half the number of odd degree ve…

math.PR2023

Euclidean minimum spanning trees with location dependent and power weighted edges

Ghurumuruhan Ganesan

Consider~\(n\) nodes~\(\{X_i\}_{1 \leq i \leq n}\) independently distributed in the unit square~\(S,\) each according to a distribution~\(f\) and let~\(K_n\) be the complete graph…

math.PR2023

Robust Domination in Random Graphs

Ghurumuruhan Ganesan

In this paper, we study "robust" dominating sets of random graphs that retain the domination property even if a small \emph{deterministic} set of edges are removed. We motivate our…

math.PR2023

Weighted Domination and Colouring in Random Graphs

Ghurumuruhan Ganesan

In the first part of this paper, we consider weighted domination in the case where the vertices of the complete graph on~\(n\) vertices are equipped with independent and identicall…

math.CO2023

Edge Constrained Eulerian Extensions

Ghurumuruhan Ganesan

In this paper we study Eulerian extensions with edge constraints and use the probabilistic method to establish sufficient conditions for a given connected graph to be a subgraph of…

math.CO2023

Redundancy of Codes with Graph Constraints

Ghurumuruhan Ganesan

In this paper, we study the redundancy of linear codes with graph constraints. First we consider linear parity check codes based on bipartite graphs with diversity and with general…

math.PR2023

Minimum Weight Random Graphs with Edge Constraints

Ghurumuruhan Ganesan

In this paper, we study two examples of minimum weight random graphs with edge constraints. First we consider the complete graph on vertices equipped with uniformly heavy edg…

math.PR2023

Coloured and Dependent Planar Matchings of Random Bipartite Graphs

Ghurumuruhan Ganesan

In this paper, we study two problems related to planar matchings in random bipartite graphs. First, we colour each edge of the complete bipartite graph uniformly randomly…