Mehrdad Farajtabar
Mehrdad Farajtabar
Research Scientist, Google DeepMind
Email verificata su google.com
TitoloCitata daAnno
Coevolve: A joint point process model for information diffusion and network co-evolution
M Farajtabar, Y Wang, MG Rodriguez, S Li, H Zha, L Song
Advances in Neural Information Processing Systems, 1954-1962, 2015
1402015
Shaping social activity by incentivizing users
M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song
Advances in neural information processing systems, 2474-2482, 2014
1162014
Dirichlet-hawkes processes with applications to clustering continuous-time document streams
N Du, M Farajtabar, A Ahmed, AJ Smola, L Song
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
902015
Learning granger causality for hawkes processes
H Xu, M Farajtabar, H Zha
International Conference on Machine Learning, 1717-1726, 2016
782016
Back to the past: Source identification in diffusion networks from partially observed cascades
M Farajtabar, M Gomez-Rodriguez, N Du, M Zamani, H Zha, L Song
Artificial Intelligence and Statistics, 2015
702015
Wasserstein learning of deep generative point process models
S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha
Advances in Neural Information Processing Systems, 3247-3257, 2017
482017
Fake news mitigation via point process based intervention
M Farajtabar, J Yang, X Ye, H Xu, R Trivedi, E Khalil, S Li, L Song, H Zha
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
452017
More robust doubly robust off-policy evaluation
M Farajtabar, Y Chow, M Ghavamzadeh
International Conference on Machine Learning (ICML), 1446-1455, 2018
412018
From local similarity to global coding: An application to image classification
A Shaban, HR Rabiee, M Farajtabar, M Ghazvininejad
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
382013
Correlated cascades: Compete or cooperate
A Zarezade, A Khodadadi, M Farajtabar, HR Rabiee, H Zha
Thirty-First AAAI Conference on Artificial Intelligence, 2017
312017
Dyrep: Learning representations over dynamic graphs
R Trivedi, M Farajtabar, P Biswal, H Zha
International Conference on Learning Representations (ICLR), 2019
29*2019
Multistage Campaigning in Social Networks
M Farajtabar, X Ye, S Harati, L Song, H Zha
Advances in Neural Information Processing Systems, 4718-4726, 2016
292016
Recurrent poisson factorization for temporal recommendation
S Hosseini, A Khodadadi, K Alizadeh, A Arabzadeh, M Farajtabar, H Zha, ...
IEEE Transactions on Knowledge and Data Engineering, 2018
282018
Smart broadcasting: Do you want to be seen?
MR Karimi, E Tavakoli, M Farajtabar, L Song, M Gomez Rodriguez
Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016
272016
Distilling information reliability and source trustworthiness from digital traces
B Tabibian, I Valera, M Farajtabar, L Song, B Schölkopf, ...
Proceedings of the 26th International Conference on World Wide Web, 847-855, 2017
232017
Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Methods
A Shaban, M Farajtabar, B Xie, L Song, B Boots
The Conference on Uncertainty in Artificial Intelligence (UAI), 2015
222015
NetCodec: Community Detection from Individual Activities
L Tran, M Farajtabar, L Song, H Zha
SIAM International Conference on Data Mining, 2015
212015
Learning time series associated event sequences with recurrent point process networks
S Xiao, J Yan, M Farajtabar, L Song, X Yang, H Zha
IEEE transactions on neural networks and learning systems, 2019
19*2019
Detecting changes in dynamic events over networks
S Li, Y Xie, M Farajtabar, A Verma, L Song
IEEE Transactions on Signal and Information Processing over Networks 3 (2 …, 2017
162017
Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher
SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh
arXiv preprint arXiv:1902.03393, 2019
142019
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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