Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh AAAI 2020, 2020 | 1066* | 2020 |
Dyrep: Learning representations over dynamic graphs R Trivedi, M Farajtabar, P Biswal, H Zha ICLR 2019, 2019 | 623* | 2019 |
Orthogonal Gradient Descent for Continual Learning M Farajtabar, N Azizan, A Mott, A Li AISTATS 2020, 2020 | 303 | 2020 |
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 | 297 | 2015 |
More robust doubly robust off-policy evaluation M Farajtabar, Y Chow, M Ghavamzadeh ICML 2018, 2018 | 270 | 2018 |
Learning granger causality for hawkes processes H Xu, M Farajtabar, H Zha ICML 2016, 2016 | 252 | 2016 |
Self-distillation amplifies regularization in hilbert space H Mobahi, M Farajtabar, PL Bartlett NeurIPS 2020, 2020 | 221 | 2020 |
Dirichlet-hawkes processes with applications to clustering continuous-time document streams N Du, M Farajtabar, A Ahmed, AJ Smola, L Song KDD 2015, 2015 | 209 | 2015 |
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 | 205 | 2017 |
Wasserstein learning of deep generative point process models S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha NeurIPS 2017, 2017 | 191 | 2017 |
Understanding the Role of Training Regimes in Continual Learning S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh NeurIPS 2020, 2020 | 185* | 2020 |
Shaping social activity by incentivizing users M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song NeurIPS 2014, 2014 | 176 | 2014 |
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 | 155* | 2019 |
Adapting auxiliary losses using gradient similarity Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ... arXiv preprint arXiv:1812.02224, 2018 | 149 | 2018 |
Linear mode connectivity in multitask and continual learning SI Mirzadeh, M Farajtabar, D Gorur, R Pascanu, H Ghasemzadeh ICLR 2021, 2021 | 106 | 2021 |
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 | 101 | 2015 |
Recurrent poisson factorization for temporal recommendation SA Hosseini, A Khodadadi, K Alizadeh, A Arabzadeh, M Farajtabar, H Zha, ... KDD 2017, 2018 | 70 | 2018 |
Correlated cascades: Compete or cooperate A Zarezade, A Khodadadi, M Farajtabar, HR Rabiee, H Zha AAAI 2017, 2017 | 68 | 2017 |
Learning to Incentivize Other Learning Agents J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha NeurIPS 2020, 2020 | 60 | 2020 |
Multistage Campaigning in Social Networks M Farajtabar, X Ye, S Harati, L Song, H Zha NeurIPS 2016, 2016 | 60 | 2016 |