ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2201.01689
  4. Cited By
Asymptotics of $\ell_2$ Regularized Network Embeddings

Asymptotics of ℓ2\ell_2ℓ2​ Regularized Network Embeddings

5 January 2022
A. Davison
ArXivPDFHTML

Papers citing "Asymptotics of $\ell_2$ Regularized Network Embeddings"

38 / 38 papers shown
Title
Asymptotics of Network Embeddings Learned via Subsampling
Asymptotics of Network Embeddings Learned via Subsampling
Andrew J. Davison
Morgane Austern
14
9
0
06 Jul 2021
Contrastive Representation Learning: A Framework and Review
Contrastive Representation Learning: A Framework and Review
Phúc H. Lê Khắc
Graham Healy
Alan F. Smeaton
SSL
AI4TS
229
697
0
10 Oct 2020
Node Embeddings and Exact Low-Rank Representations of Complex Networks
Node Embeddings and Exact Low-Rank Representations of Complex Networks
Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
BDL
121
34
0
10 Jun 2020
Contrastive Multi-View Representation Learning on Graphs
Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani
Amir Hosein Khas Ahmadi
SSL
168
1,284
0
10 Jun 2020
Limit theorems for out-of-sample extensions of the adjacency and
  Laplacian spectral embeddings
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith D. Levin
Fred Roosta
M. Tang
Michael W. Mahoney
Carey E. Priebe
18
5
0
29 Sep 2019
Revealing Network Structure, Confidentially: Improved Rates for
  Node-Private Graphon Estimation
Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation
C. Borgs
J. Chayes
Adam D. Smith
Ilias Zadik
FedML
49
46
0
04 Oct 2018
Deep Graph Infomax
Deep Graph Infomax
Petar Velickovic
W. Fedus
William L. Hamilton
Pietro Lio
Yoshua Bengio
R. Devon Hjelm
GNN
102
2,359
0
27 Sep 2018
Empirical Risk Minimization and Stochastic Gradient Descent for
  Relational Data
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Victor Veitch
Morgane Austern
Wenda Zhou
David M. Blei
Peter Orbanz
19
9
0
27 Jun 2018
On the Convergence of Stochastic Gradient Descent with Adaptive
  Stepsizes
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyun Li
Francesco Orabona
51
294
0
21 May 2018
Network Representation Using Graph Root Distributions
Network Representation Using Graph Root Distributions
Jing Lei
72
31
0
27 Feb 2018
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE,
  and node2vec
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
J. Qiu
Yuxiao Dong
Hao Ma
Jian Li
Kuansan Wang
Jie Tang
46
916
0
09 Oct 2017
Representation Learning on Graphs: Methods and Applications
Representation Learning on Graphs: Methods and Applications
William L. Hamilton
Rex Ying
J. Leskovec
GNN
106
1,970
0
17 Sep 2017
A statistical interpretation of spectral embedding: the generalised
  random dot product graph
A statistical interpretation of spectral embedding: the generalised random dot product graph
Patrick Rubin-Delanchy
Joshua Cape
M. Tang
Carey E. Priebe
37
129
0
16 Sep 2017
Statistical inference on random dot product graphs: a survey
Statistical inference on random dot product graphs: a survey
A. Athreya
D. E. Fishkind
Keith D. Levin
V. Lyzinski
Youngser Park
Yichen Qin
D. Sussman
M. Tang
Joshua T. Vogelstein
Carey E. Priebe
76
248
0
16 Sep 2017
Rates of Convergence of Spectral Methods for Graphon Estimation
Rates of Convergence of Spectral Methods for Graphon Estimation
Jiaming Xu
78
81
0
10 Sep 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
364
15,066
0
07 Jun 2017
Graph Embedding Techniques, Applications, and Performance: A Survey
Graph Embedding Techniques, Applications, and Performance: A Survey
Palash Goyal
Emilio Ferrara
GNN
AI4TS
78
1,723
0
08 May 2017
On the sub-Gaussianity of the Beta and Dirichlet distributions
On the sub-Gaussianity of the Beta and Dirichlet distributions
Olivier Marchal
Julyan Arbel
18
79
0
28 Apr 2017
Variational Graph Auto-Encoders
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
GNN
BDL
SSL
CML
90
3,541
0
21 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
411
28,795
0
09 Sep 2016
Limit theorems for eigenvectors of the normalized Laplacian for random
  graphs
Limit theorems for eigenvectors of the normalized Laplacian for random graphs
M. Tang
Carey E. Priebe
28
99
0
28 Jul 2016
node2vec: Scalable Feature Learning for Networks
node2vec: Scalable Feature Learning for Networks
Aditya Grover
J. Leskovec
142
10,800
0
03 Jul 2016
Optimization Methods for Large-Scale Machine Learning
Optimization Methods for Large-Scale Machine Learning
Léon Bottou
Frank E. Curtis
J. Nocedal
165
3,191
0
15 Jun 2016
The Class of Random Graphs Arising from Exchangeable Random Measures
The Class of Random Graphs Arising from Exchangeable Random Measures
Victor Veitch
Daniel M. Roy
103
102
0
07 Dec 2015
Oracle inequalities for network models and sparse graphon estimation
Oracle inequalities for network models and sparse graphon estimation
Olga Klopp
Alexandre B. Tsybakov
Nicolas Verzelen MODAL'X
168
134
0
15 Jul 2015
Private Graphon Estimation for Sparse Graphs
Private Graphon Estimation for Sparse Graphs
C. Borgs
J. Chayes
Adam D. Smith
120
87
0
19 Jun 2015
LINE: Large-scale Information Network Embedding
LINE: Large-scale Information Network Embedding
Jian Tang
Meng Qu
Mingzhe Wang
Ming Zhang
Jun Yan
Qiaozhu Mei
GNN
102
5,315
0
12 Mar 2015
Rate-optimal graphon estimation
Rate-optimal graphon estimation
Chao Gao
Yu Lu
Harrison H. Zhou
80
217
0
21 Oct 2014
Generalized Low Rank Models
Generalized Low Rank Models
Madeleine Udell
Corinne Horn
R. Zadeh
Stephen P. Boyd
52
345
0
01 Oct 2014
DeepWalk: Online Learning of Social Representations
DeepWalk: Online Learning of Social Representations
Bryan Perozzi
Rami Al-Rfou
Steven Skiena
HAI
204
9,735
0
26 Mar 2014
Consistency of spectral clustering in stochastic block models
Consistency of spectral clustering in stochastic block models
Jing Lei
Alessandro Rinaldo
90
603
0
07 Dec 2013
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
264
33,445
0
16 Oct 2013
Nonparametric graphon estimation
Nonparametric graphon estimation
P. Wolfe
S. Olhede
75
202
0
23 Sep 2013
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic
  Programming
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming
Saeed Ghadimi
Guanghui Lan
ODL
54
1,538
0
22 Sep 2013
Matrix estimation by Universal Singular Value Thresholding
Matrix estimation by Universal Singular Value Thresholding
S. Chatterjee
195
523
0
06 Dec 2012
Nuclear norm penalization and optimal rates for noisy low rank matrix
  completion
Nuclear norm penalization and optimal rates for noisy low rank matrix completion
V. Koltchinskii
Alexandre B. Tsybakov
Karim Lounici
110
663
0
29 Nov 2010
Consistency of trace norm minimization
Consistency of trace norm minimization
Francis R. Bach
183
220
0
15 Oct 2007
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear
  Norm Minimization
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
Benjamin Recht
Maryam Fazel
P. Parrilo
185
3,758
0
28 Jun 2007
1