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Mihai Cucuringu

11 papers hereh-index 10634 citations16 works total

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

author position
  • sole author2
  • first author7
  • last author1

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.SI4
  • cs.CE2
  • cs.LG2
  • cs.DM1
  • stat.ML1
  • stat.OT1
same name
  • Mihai Cucuringu — 29 papers, h 12
  • Mihai Cucuringu — 20 papers, h 11
  • Mihai Cucuringu — 12 papers, h 8
  • Mihai Cucuringu — 5 papers, h 3
  • Mihai Cucuringu — 5 papers, h 2
  • Mihai Cucuringu — 3 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
20092016
most citedEigenvector Synchronization, Graph Rigidity and the Molecule Problem

43 citations · 118 across the 9 of their papers we have counts for

collaborators
Showing cs.SIShow all

4 papers · 1 filter

cs.SI2016★ 4 cited

Scalable Constrained Clustering: A Generalized Spectral Method

Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla +2

We present a simple spectral approach to the well-studied constrained clustering problem. It captures constrained clustering as a generalized eigenvalue problem with graph Laplacia…

cs.SI2015★ 24 cited

Synchronization over Z2​ and community detection in multiplex signed networks with constraints

Mihai Cucuringu

Finding group elements from noisy measurements of their pairwise ratios is also known as the group synchronization problem, first introduced in the context of the group SO(2) of pl…

cs.SI2015★ 6 cited

Scalable Constrained Clustering: A Generalized Spectral Method

Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla

We present a principled spectral approach to the well-studied constrained clustering problem. It reduces clustering to a generalized eigenvalue problem on Laplacians. The method wo…

cs.SI2011

Extracting spatial information from networks with low-order eigenvectors

Mihai Cucuringu, Vincent D. Blondel, Paul Van Dooren

We consider the problem of inferring meaningful spatial information in networks from incomplete information on the connection intensity between the nodes of the network. We conside…

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