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Spectral Theory of Unsigned and Signed Graphs. Applications to Graph
  Clustering: a Survey

Spectral Theory of Unsigned and Signed Graphs. Applications to Graph Clustering: a Survey

18 January 2016
J. Gallier
ArXiv (abs)PDFHTML

Papers citing "Spectral Theory of Unsigned and Signed Graphs. Applications to Graph Clustering: a Survey"

16 / 16 papers shown
A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Version
A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended VersionInternational Conference on Conceptual Structures (ICCS), 2025
Mieczysław A. Kłopotek
Sławomir T. Wierzchoń
B. Starosta
Dariusz Czerski
P. Borkowski
232
3
0
16 Apr 2025
Enabling Tensor Decomposition for Time-Series Classification via A
  Simple Pseudo-Laplacian Contrast
Enabling Tensor Decomposition for Time-Series Classification via A Simple Pseudo-Laplacian Contrast
Man Li
Ziyue Li
Lijun Sun
Fugee Tsung
AI4TS
364
2
0
23 Sep 2024
Two Trades is not Baffled: Condensing Graph via Crafting Rational
  Gradient Matching
Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching
Tianle Zhang
Yuchen Zhang
Kun Wang
Kai Wang
Beining Yang
Kaipeng Zhang
Wenqi Shao
Ping Liu
Qiufeng Wang
Yang You
DD
465
15
0
07 Feb 2024
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted
  Graph Convolutional Neural Networks
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
Steffen Jung
Margret Keuper
GNN
197
4
0
04 Apr 2022
Graph similarity learning for change-point detection in dynamic networks
Graph similarity learning for change-point detection in dynamic networksMachine-mediated learning (ML), 2022
Déborah Sulem
Henry Kenlay
Mihai Cucuringu
Xiaowen Dong
300
31
0
29 Mar 2022
Regularized spectral methods for clustering signed networks
Regularized spectral methods for clustering signed networks
Mihai Cucuringu
A. Singh
Déborah Sulem
Hemant Tyagi
236
23
0
03 Nov 2020
The Mathematical Foundations of Manifold Learning
The Mathematical Foundations of Manifold Learning
Luke Melas-Kyriazi
AI4CE
265
20
0
30 Oct 2020
Decoupled Variational Embedding for Signed Directed Networks
Decoupled Variational Embedding for Signed Directed NetworksACM Transactions on the Web (TWEB), 2020
Xu Chen
Jiangchao Yao
Maosen Li
Ya Zhang
Yanfeng Wang
199
5
0
28 Aug 2020
A literature survey of matrix methods for data science
A literature survey of matrix methods for data scienceGAMM-Mitteilungen (GAMM), 2019
Martin Stoll
322
22
0
17 Dec 2019
Spectral Clustering of Signed Graphs via Matrix Power Means
Spectral Clustering of Signed Graphs via Matrix Power MeansInternational Conference on Machine Learning (ICML), 2019
Pedro Mercado
Francesco Tudisco
Matthias Hein
278
37
0
15 May 2019
An MBO scheme for clustering and semi-supervised clustering of signed
  networks
An MBO scheme for clustering and semi-supervised clustering of signed networks
Mihai Cucuringu
A. Pizzoferrato
Y. Gennip
498
16
0
10 Jan 2019
Node Classification for Signed Social Networks Using Diffuse Interface
  Methods
Node Classification for Signed Social Networks Using Diffuse Interface Methods
Pedro Mercado
J. Bosch
Martin Stoll
259
5
0
07 Sep 2018
Seating Assignment Using Constrained Signed Spectral Clustering
Seating Assignment Using Constrained Signed Spectral Clustering
João Sedoc
Aline Normoyle
122
0
0
02 Aug 2017
On spectral partitioning of signed graphs
On spectral partitioning of signed graphs
A. Knyazev
233
32
0
05 Jan 2017
Generalizing diffuse interface methods on graphs: non-smooth potentials
  and hypergraphs
Generalizing diffuse interface methods on graphs: non-smooth potentials and hypergraphs
J. Bosch
Steffen Klamt
Martin Stoll
196
24
0
18 Nov 2016
Semantic Word Clusters Using Signed Normalized Graph Cuts
Semantic Word Clusters Using Signed Normalized Graph Cuts
João Sedoc
J. Gallier
L. Ungar
Dean Phillips Foster
157
9
0
20 Jan 2016
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