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Mehrdad Farajtabar
Mehrdad Farajtabar
Google DeepMind
Bestätigte E-Mail-Adresse bei google.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher
SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh
AAAI 2020, 2020
382*2020
Dyrep: Learning representations over dynamic graphs
R Trivedi, M Farajtabar, P Biswal, H Zha
ICLR 2019, 2019
247*2019
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
JMLR 2016, 2015
2342015
Learning granger causality for hawkes processes
H Xu, M Farajtabar, H Zha
ICML 2016, 2016
1842016
Dirichlet-hawkes processes with applications to clustering continuous-time document streams
N Du, M Farajtabar, A Ahmed, AJ Smola, L Song
KDD 2015, 2015
1762015
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
ICML 2017, 2017
1612017
More robust doubly robust off-policy evaluation
M Farajtabar, Y Chow, M Ghavamzadeh
ICML 2018, 2018
1602018
Shaping social activity by incentivizing users
M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song
NeurIPS 2014, 2014
1542014
Wasserstein learning of deep generative point process models
S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha
NeurIPS 2017, 2017
1392017
Orthogonal Gradient Descent for Continual Learning
M Farajtabar, N Azizan, A Mott, A Li
AISTATS 2020, 2020
992020
Back to the past: Source identification in diffusion networks from partially observed cascades
M Farajtabar, MG Rodriguez, M Zamani, N Du, H Zha, L Song
AISTATS 2015, 2015
902015
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 30 (10), 3124-3136, 2019
88*2019
Self-distillation amplifies regularization in hilbert space
H Mobahi, M Farajtabar, PL Bartlett
NeurIPS 2020, 2020
832020
Adapting auxiliary losses using gradient similarity
Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ...
arXiv preprint arXiv:1812.02224, 2018
792018
Understanding the Role of Training Regimes in Continual Learning
S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh
NeurIPS 2020, 2020
59*2020
Correlated cascades: Compete or cooperate
A Zarezade, A Khodadadi, M Farajtabar, HR Rabiee, H Zha
AAAI 2017, 2017
552017
Recurrent poisson factorization for temporal recommendation
SA Hosseini, A Khodadadi, K Alizadeh, A Arabzadeh, M Farajtabar, H Zha, ...
KDD 2017, 2018
542018
Multistage Campaigning in Social Networks
M Farajtabar, X Ye, S Harati, L Song, H Zha
NeurIPS 2016, 2016
522016
NetCodec: Community Detection from Individual Activities
L Tran, M Farajtabar, L Song, H Zha
SIAM International Conference on Data Mining, 2015
412015
Learning Conditional Generative Models for Temporal Point Processes.
S Xiao, H Xu, J Yan, M Farajtabar, X Yang, L Song, H Zha
AAAI 2018, 2018
402018
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