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Inferring Networks of Diffusion and Influence
v1v2v3 (latest)

Inferring Networks of Diffusion and Influence

1 June 2010
Manuel Gomez Rodriguez
J. Leskovec
Andreas Krause
ArXiv (abs)PDFHTML

Papers citing "Inferring Networks of Diffusion and Influence"

21 / 121 papers shown
COEVOLVE: A Joint Point Process Model for Information Diffusion and
  Network Co-evolution
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolutionNeural Information Processing Systems (NeurIPS), 2015
Mehrdad Farajtabar
Yichen Wang
Manuel Gomez Rodriguez
Shuang Li
H. Zha
Le Song
214
244
0
08 Jul 2015
Inferring Graphs from Cascades: A Sparse Recovery Framework
Inferring Graphs from Cascades: A Sparse Recovery FrameworkInternational Conference on Machine Learning (ICML), 2015
Jean Pouget-Abadie
Thibaut Horel
179
53
0
21 May 2015
Learning and Optimization with Submodular Functions
Learning and Optimization with Submodular Functions
Bharathwaj Sankaran
Marjan Ghazvininejad
Xinran He
David C. Kale
L. Cohen
121
2
0
07 May 2015
Influence Maximization with Bandits
Influence Maximization with Bandits
Sharan Vaswani
L. Lakshmanan
Mark Schmidt
258
65
0
27 Feb 2015
Distributed Submodular Maximization
Distributed Submodular Maximization
Baharan Mirzasoleiman
Amin Karbasi
Rik Sarkar
Andreas Krause
322
209
0
03 Nov 2014
Lazier Than Lazy Greedy
Lazier Than Lazy GreedyAAAI Conference on Artificial Intelligence (AAAI), 2014
Baharan Mirzasoleiman
Ashwinkumar Badanidiyuru
Amin Karbasi
J. Vondrák
Andreas Krause
316
440
0
28 Sep 2014
How good is the Shapley value-based approach to the influence
  maximization problem?
How good is the Shapley value-based approach to the influence maximization problem?European Conference on Artificial Intelligence (ECAI), 2014
Kamil Adamczewski
Szymon Matejczyk
Tomasz P. Michalak
TDIFAtt
93
8
0
27 Sep 2014
Estimating Diffusion Network Structures: Recovery Conditions, Sample
  Complexity & Soft-thresholding Algorithm
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding AlgorithmInternational Conference on Machine Learning (ICML), 2014
Hadi Daneshmand
Manuel Gomez Rodriguez
Le Song
Bernhard Schölkopf
TPM
180
124
0
12 May 2014
Discovering Latent Network Structure in Point Process Data
Discovering Latent Network Structure in Point Process DataInternational Conference on Machine Learning (ICML), 2014
Scott W. Linderman
Ryan P. Adams
309
284
0
04 Feb 2014
Modeling Emotion Influence from Images in Social Networks
Modeling Emotion Influence from Images in Social Networks
Xiaohui Wang
Jia Jia
Lianhong Cai
Jie Tang
68
4
0
17 Jan 2014
Budgeted Influence Maximization for Multiple Products
Budgeted Influence Maximization for Multiple Products
Nan Du
Yingyu Liang
Maria-Florina Balcan
Le Song
172
13
0
08 Dec 2013
Scalable Influence Estimation in Continuous-Time Diffusion Networks
Scalable Influence Estimation in Continuous-Time Diffusion NetworksNeural Information Processing Systems (NeurIPS), 2013
Nan Du
Le Song
Manuel Gomez Rodriguez
H. Zha
217
269
0
14 Nov 2013
Modeling Information Propagation with Survival Theory
Modeling Information Propagation with Survival TheoryInternational Conference on Machine Learning (ICML), 2013
Manuel Gomez Rodriguez
J. Leskovec
Bernhard Schölkopf
182
183
0
15 May 2013
Latent Self-Exciting Point Process Model for Spatial-Temporal Networks
Latent Self-Exciting Point Process Model for Spatial-Temporal Networks
Yoon-Sik Cho
Aram Galstyan
Jeff Brantingham
George E. Tita
278
43
0
12 Feb 2013
Diffusion of Lexical Change in Social Media
Diffusion of Lexical Change in Social MediaPLoS ONE (PLOS ONE), 2012
Jacob Eisenstein
Brendan O'Connor
Noah A. Smith
Eric Xing
363
256
0
18 Oct 2012
Inferring the Underlying Structure of Information Cascades
Inferring the Underlying Structure of Information Cascades
Bo Zong
Yinghui Wu
Ambuj K. Singh
Xifeng Yan
128
18
0
12 Oct 2012
Learning the Structure and Parameters of Large-Population Graphical
  Games from Behavioral Data
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral DataJournal of machine learning research (JMLR), 2012
Jean Honorio
Luis E. Ortiz
CML
444
40
0
16 Jun 2012
Finding the Graph of Epidemic Cascades
Finding the Graph of Epidemic Cascades
Praneeth Netrapalli
Sujay Sanghavi
216
18
0
08 Feb 2012
Composite Social Network for Predicting Mobile Apps Installation
Composite Social Network for Predicting Mobile Apps InstallationAAAI Conference on Artificial Intelligence (AAAI), 2011
Wei Pan
Nadav Aharony
Alex Pentland
213
127
0
02 Jun 2011
Supervised Random Walks: Predicting and Recommending Links in Social
  Networks
Supervised Random Walks: Predicting and Recommending Links in Social Networks
L. Backstrom
J. Leskovec
279
1,143
0
17 Nov 2010
Reconstruction of Causal Networks by Set Covering
Reconstruction of Causal Networks by Set Covering
Nick Fyson
T. D. Bie
N. Cristianini
CML
140
3
0
04 Jun 2010
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