Mehrdad Farajtabar

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Hongyuan ZhaThe Chinese University of Hong Kong, ShenzhenPatvirtintas el. paštas cuhk.edu.cn
Iman MirzadehApplePatvirtintas el. paštas apple.com
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligencePatvirtintas el. paštas biomap.com
Ang Lisimular.aiPatvirtintas el. paštas angli.ai
Razvan PascanuGoogle DeepMindPatvirtintas el. paštas google.com
Oncel TuzelApplePatvirtintas el. paštas apple.com
Mohammad RastegariDistinguished AI Scientist at Meta Inc.Patvirtintas el. paštas cs.washington.edu
Sachin MehtaAI/ML Applied Research Scientist at Apple Inc.Patvirtintas el. paštas apple.com
Manuel Gomez RodriguezFaculty, Max Planck Institute for Software Systems (MPI-SWS)Patvirtintas el. paštas mpi-sws.org
Dong YinResearch Scientist, ApplePatvirtintas el. paštas apple.com
Fartash FaghriApple ML ResearchPatvirtintas el. paštas cs.toronto.edu
Keivan Alizadeh-VahidUniversity of WashingtonPatvirtintas el. paštas uw.edu
Rakshit TrivediMassachusetts Institute of TechnologyPatvirtintas el. paštas csail.mit.edu
Hadi PouransariApple, Stanford UniversityPatvirtintas el. paštas stanford.edu
Raviteja VemulapalliMachine Learning Researcher at ApplePatvirtintas el. paštas apple.com
Dilan GorurDeepMindPatvirtintas el. paštas google.com
Hamid R. RabieeDistinguished Professor of Computer Engineering, Sharif University of TechnologyPatvirtintas el. paštas sharif.edu
NAN DUAI and Machine Learning Research, ApplePatvirtintas el. paštas apple.com
Amirreza ShabanApplied Research Scientists, CruisePatvirtintas el. paštas uw.edu
Arslan ChaudhryDeepMindPatvirtintas el. paštas deepmind.com

Stebėti

Mehrdad Farajtabar

Research Scientist at Apple

Patvirtintas el. paštas apple.com - Pagrindinis puslapis

Machine Learning Large Language Models Multimodal Models Efficient ML Continual Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh AAAI 2020, 2020	1284*	2020
Dyrep: Learning representations over dynamic graphs R Trivedi, M Farajtabar, P Biswal, H Zha ICLR 2019, 2019	711*	2019
Orthogonal Gradient Descent for Continual Learning M Farajtabar, N Azizan, A Mott, A Li AISTATS 2020, 2020	374	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	307	2015
More robust doubly robust off-policy evaluation M Farajtabar, Y Chow, M Ghavamzadeh ICML 2018, 2018	288	2018
Learning granger causality for hawkes processes H Xu, M Farajtabar, H Zha ICML 2016, 2016	265	2016
Self-distillation amplifies regularization in hilbert space H Mobahi, M Farajtabar, PL Bartlett NeurIPS 2020, 2020	253	2020
Understanding the Role of Training Regimes in Continual Learning S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh NeurIPS 2020, 2020	222*	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	217	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	213	2015
Wasserstein learning of deep generative point process models S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha NeurIPS 2017, 2017	207	2017
Shaping social activity by incentivizing users M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song NeurIPS 2014, 2014	180	2014
Adapting auxiliary losses using gradient similarity Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ... arXiv preprint arXiv:1812.02224, 2018	169	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	164*	2019
Linear mode connectivity in multitask and continual learning SI Mirzadeh, M Farajtabar, D Gorur, R Pascanu, H Ghasemzadeh ICLR 2021, 2021	128	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	101	2023
Learning to Incentivize Other Learning Agents J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha NeurIPS 2020, 2020	73	2020
Recurrent poisson factorization for temporal recommendation SA Hosseini, A Khodadadi, K Alizadeh, A Arabzadeh, M Farajtabar, H Zha, ... KDD 2017, 2018	73	2018
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	72	2023

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