Mehrdad Farajtabar

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Citations	6761	5721
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Hongyuan ZhaThe Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Iman MirzadehAppleVerified email at apple.com
Le SongGenBio AI, Mohamed bin Zayed University of Artificial IntelligenceVerified email at mbzuai.ac.ae
Ang Lisimular.aiVerified email at angli.ai
Razvan PascanuGoogle DeepMindVerified email at google.com
Oncel TuzelAppleVerified email at apple.com
Mohammad RastegariDistinguished AI Scientist at Meta Inc.Verified email at cs.washington.edu
Sachin MehtaAI/ML Applied Research Scientist at Apple Inc.Verified email at apple.com
Manuel Gomez RodriguezFaculty, Max Planck Institute for Software Systems (MPI-SWS)Verified email at mpi-sws.org
Fartash FaghriApple ML ResearchVerified email at cs.toronto.edu
Keivan Alizadeh-VahidUniversity of WashingtonVerified email at uw.edu
Dong YinResearch Scientist, AppleVerified email at apple.com
Rakshit TrivediMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Raviteja VemulapalliMachine Learning Researcher at AppleVerified email at apple.com
Hadi PouransariApple, Stanford UniversityVerified email at stanford.edu
Dilan GorurDeepMindVerified email at google.com
Hamid R. RabieeDistinguished Professor of Computer Engineering, Sharif University of TechnologyVerified email at sharif.edu
NAN DUAI and Machine Learning Research, AppleVerified email at apple.com
Amirreza ShabanApplied Research Scientists, CruiseVerified email at uw.edu
Arslan ChaudhryDeepMindVerified email at deepmind.com

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	1348*	2020
Dyrep: Learning representations over dynamic graphs R Trivedi, M Farajtabar, P Biswal, H Zha ICLR 2019, 2019	746*	2019
Orthogonal Gradient Descent for Continual Learning M Farajtabar, N Azizan, A Mott, A Li AISTATS 2020, 2020	390	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	314	2015
More robust doubly robust off-policy evaluation M Farajtabar, Y Chow, M Ghavamzadeh ICML 2018, 2018	292	2018
Learning granger causality for hawkes processes H Xu, M Farajtabar, H Zha ICML 2016, 2016	275	2016
Self-distillation amplifies regularization in hilbert space H Mobahi, M Farajtabar, PL Bartlett NeurIPS 2020, 2020	267	2020
Understanding the Role of Training Regimes in Continual Learning S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh NeurIPS 2020, 2020	230*	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	222	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	214	2015
Wasserstein learning of deep generative point process models S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha NeurIPS 2017, 2017	210	2017
Shaping social activity by incentivizing users M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song NeurIPS 2014, 2014	182	2014
Adapting auxiliary losses using gradient similarity Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ... arXiv preprint arXiv:1812.02224, 2018	173	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	166*	2019
Linear mode connectivity in multitask and continual learning SI Mirzadeh, M Farajtabar, D Gorur, R Pascanu, H Ghasemzadeh ICLR 2021, 2021	133	2021
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	126	2023
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	104	2015
Llm in a flash: Efficient large language model inference with limited memory K Alizadeh, I Mirzadeh, D Belenko, K Khatamifard, M Cho, CC Del Mundo, ... arXiv preprint arXiv:2312.11514, 2023	88	2023
Gsm-symbolic: Understanding the limitations of mathematical reasoning in large language models I Mirzadeh, K Alizadeh, H Shahrokhi, O Tuzel, S Bengio, M Farajtabar arXiv preprint arXiv:2410.05229, 2024	85	2024
Learning to Incentivize Other Learning Agents J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha NeurIPS 2020, 2020	77	2020

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