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researcher

N. Srivastava

33 papers hereh-index 213.9k citations57 works total

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

author position
  • sole author1
  • first author2
  • middle author3
  • last author27

Across the 33 of 33 papers where every author was matched, so the position is known.

fields
  • math.CO8
  • cs.DS7
  • math.PR6
  • math.FA5
  • math.NA2
  • cs.DM1
same name
  • N. Srivastava — 26 papers, h 23
  • N. Srivastava — 13 papers, h 4
  • N. Srivastava — 10 papers, h 10
  • N. Srivastava — 2 papers, h 16
  • N. Srivastava — 2 papers, h 5
  • N. Srivastava — 1 paper, h 8

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
20082023
most citedCovariance estimation for distributions with 2+ε moments

72 citations · 174 across the 24 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

math.CO2020★ 1 cited

Support of Closed Walks and Second Eigenvalue Multiplicity of the Normalized Adjacency Matrix

Theo McKenzie, Peter M. R. Rasmussen, Nikhil Srivastava

We show that the multiplicity of the second normalized adjacency matrix eigenvalue of any connected graph of maximum degree Δ is bounded by O(nΔ7/5/log1/5−o(1)n) for an…

math.PR2020★ 1 cited

Scalar Poincaré Implies Matrix Poincaré

Ankit Garg, Tarun Kathuria, Nikhil Srivastava

We prove that every reversible Markov semigroup which satisfies a Poincaré inequality satisfies a matrix-valued Poincaré inequality for Hermitian d×d matrix valued function…

math.PR2020★ 2 cited

Overlaps, Eigenvalue Gaps, and Pseudospectrum under real Ginibre and Absolutely Continuous Perturbations

Jess Banks, Jorge Garza Vargas, Archit Kulkarni +1

Let Gn​ be an n×n matrix with real i.i.d. N(0,1/n) entries, let A be a real n×n matrix with ∥A∥≤1, and let γ∈(0,1). We show that with p…

math.PR2020★ 4 cited

On Concentration Inequalities for Random Matrix Products

Tarun Kathuria, Satyaki Mukherjee, Nikhil Srivastava

Consider n complex random matrices X1​,…,Xn​ of size d×d sampled i.i.d. from a distribution with mean E[X]=μ. While the concentration of averages of these matric…

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