Seuraa
Mehrdad Farajtabar
Mehrdad Farajtabar
Research Scientist at Apple
Vahvistettu sähköpostiosoite verkkotunnuksessa apple.com - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Improved knowledge distillation via teacher assistant: Bridging the gap between student and teacher
SI Mirzadeh, M Farajtabar, A Li, H Ghasemzadeh
AAAI 2020, 2020
1353*2020
Dyrep: Learning representations over dynamic graphs
R Trivedi, M Farajtabar, P Biswal, H Zha
ICLR 2019, 2019
749*2019
Orthogonal Gradient Descent for Continual Learning
M Farajtabar, N Azizan, A Mott, A Li
AISTATS 2020, 2020
3952020
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
3152015
More robust doubly robust off-policy evaluation
M Farajtabar, Y Chow, M Ghavamzadeh
ICML 2018, 2018
2972018
Learning granger causality for hawkes processes
H Xu, M Farajtabar, H Zha
ICML 2016, 2016
2762016
Self-distillation amplifies regularization in hilbert space
H Mobahi, M Farajtabar, PL Bartlett
NeurIPS 2020, 2020
2702020
Understanding the Role of Training Regimes in Continual Learning
S Iman Mirzadeh, M Farajtabar, R Pascanu, H Ghasemzadeh
NeurIPS 2020, 2020
232*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
2242017
Dirichlet-hawkes processes with applications to clustering continuous-time document streams
N Du, M Farajtabar, A Ahmed, AJ Smola, L Song
KDD 2015, 2015
2142015
Wasserstein learning of deep generative point process models
S Xiao, M Farajtabar, X Ye, J Yan, L Song, H Zha
NeurIPS 2017, 2017
2112017
Shaping social activity by incentivizing users
M Farajtabar, N Du, MG Rodriguez, I Valera, H Zha, L Song
NeurIPS 2014, 2014
1822014
Adapting auxiliary losses using gradient similarity
Y Du, WM Czarnecki, SM Jayakumar, M Farajtabar, R Pascanu, ...
arXiv preprint arXiv:1812.02224, 2018
1742018
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
1332021
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
1292023
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
1042015
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
1012024
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
902023
Learning to Incentivize Other Learning Agents
J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha
NeurIPS 2020, 2020
792020
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Artikkelit 1–20