Mehrdad Farajtabar

Cited by

	All	Since 2019
Citations	6032	5338
h-index	33	30
i10-index	44	41

1300

650

325

975

201520162017201820192020202120222023202438 104 231 290 342 595 823 1062 1263 1242

Public access

View all

20 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Hongyuan ZhaThe Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Iman MirzadehAppleVerified email at apple.com
Ang Lisimular.aiVerified email at angli.ai
Razvan PascanuGoogle DeepMindVerified email at google.com
Manuel Gomez RodriguezFaculty, Max Planck Institute for Software Systems (MPI-SWS)Verified email at mpi-sws.org
Mohammad RastegariDistinguished AI Scientist at Meta Inc.Verified email at cs.washington.edu
Rakshit TrivediMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Sachin MehtaAI/ML Applied Research Scientist at Apple Inc.Verified email at apple.com
Oncel TuzelAppleVerified email at apple.com
Dong YinResearch Scientist, AppleVerified email at apple.com
Fartash FaghriApple ML ResearchVerified email at cs.toronto.edu
Hamid R. RabieeDistinguished Professor of Computer Engineering, Sharif University of TechnologyVerified email at sharif.edu
Dilan GorurDeepMindVerified email at google.com
NAN DUAI and Machine Learning Research, AppleVerified email at apple.com
Keivan Alizadeh-VahidUniversity of WashingtonVerified email at uw.edu
Raviteja VemulapalliMachine Learning Researcher at AppleVerified email at apple.com
Hadi PouransariApple, Stanford UniversityVerified email at stanford.edu
Amirreza ShabanApplied Research Scientists, CruiseVerified email at uw.edu
Isabel ValeraSaarland University and Max Planck Institute for Software SystemsVerified email at cs.uni-saarland.de

Mehrdad Farajtabar

Research Scientist at Apple

Verified email at apple.com - Homepage

Machine Learning Large Language Models Multimodal Models Efficient ML Continual Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh AAAI 2020, 2020	1193*	2020
Dyrep: Learning representations over dynamic graphs R Trivedi, M Farajtabar, P Biswal, H Zha ICLR 2019, 2019	672*	2019
Orthogonal Gradient Descent for Continual Learning M Farajtabar, N Azizan, A Mott, A Li AISTATS 2020, 2020	352	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	303	2015
More robust doubly robust off-policy evaluation M Farajtabar, Y Chow, M Ghavamzadeh ICML 2018, 2018	281	2018
Learning granger causality for hawkes processes H Xu, M Farajtabar, H Zha ICML 2016, 2016	257	2016
Self-distillation amplifies regularization in hilbert space H Mobahi, M Farajtabar, PL Bartlett NeurIPS 2020, 2020	234	2020
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	212	2017
Dirichlet-hawkes processes with applications to clustering continuous-time document streams N Du, M Farajtabar, A Ahmed, AJ Smola, L Song KDD 2015, 2015	211	2015
Understanding the Role of Training Regimes in Continual Learning S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh NeurIPS 2020, 2020	206*	2020
Wasserstein learning of deep generative point process models S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha NeurIPS 2017, 2017	200	2017
Shaping social activity by incentivizing users M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song NeurIPS 2014, 2014	178	2014
Adapting auxiliary losses using gradient similarity Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ... arXiv preprint arXiv:1812.02224, 2018	162	2018
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	159*	2019
Linear mode connectivity in multitask and continual learning SI Mirzadeh, M Farajtabar, D Gorur, R Pascanu, H Ghasemzadeh ICLR 2021, 2021	119	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	103	2015
Sam-clip: Merging vision foundation models towards semantic and spatial understanding H Wang, PKA Vasu, F Faghri, R Vemulapalli, M Farajtabar, S Mehta, ... CVPR workshop 2024, 2023	74	2023
Recurrent poisson factorization for temporal recommendation SA Hosseini, A Khodadadi, K Alizadeh, A Arabzadeh, M Farajtabar, H Zha, ... KDD 2017, 2018	71	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	66	2020

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors