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Hamed Hassani
Hamed Hassani
University of Pennsylvania (EE, CS, Stat)
Verifisert e-postadresse på seas.upenn.edu - Startside
Tittel
Sitert av
Sitert av
År
Fedpaq: A communication-efficient federated learning method with periodic averaging and quantization
A Reisizadeh, A Mokhtari, H Hassani, A Jadbabaie, R Pedarsani
International conference on artificial intelligence and statistics, 2021-2031, 2020
9432020
Exploiting shared representations for personalized federated learning
L Collins, H Hassani, A Mokhtari, S Shakkottai
International conference on machine learning, 2089-2099, 2021
8482021
Efficient and accurate estimation of lipschitz constants for deep neural networks
M Fazlyab, A Robey, H Hassani, M Morari, G Pappas
Advances in neural information processing systems 32, 2019
5422019
Jailbreaking black box large language models in twenty queries
P Chao, A Robey, E Dobriban, H Hassani, GJ Pappas, E Wong
arXiv preprint arXiv:2310.08419, 2023
5052023
Smoothllm: Defending large language models against jailbreaking attacks
A Robey, E Wong, H Hassani, GJ Pappas
arXiv preprint arXiv:2310.03684, 2023
2492023
Finite-length scaling of polar codes
SH Hassani, K Alishahi, R Urbanke
arXiv preprint arXiv:1304.4778, 2013
218*2013
Fast and provably good seedings for k-means
O Bachem, M Lucic, H Hassani, A Krause
Advances in neural information processing systems 29, 2016
2082016
Linear convergence in federated learning: Tackling client heterogeneity and sparse gradients
A Mitra, R Jaafar, GJ Pappas, H Hassani
Advances in Neural Information Processing Systems 34, 14606-14619, 2021
197*2021
Age of information in random access channels
X Chen, K Gatsis, H Hassani, SS Bidokhti
IEEE Transactions on Information Theory 68 (10), 6548-6568, 2022
1902022
An exact quantized decentralized gradient descent algorithm
A Reisizadeh, A Mokhtari, H Hassani, R Pedarsani
IEEE Transactions on Signal Processing 67 (19), 4934-4947, 2019
189*2019
Approximate k-means++ in sublinear time
O Bachem, M Lucic, SH Hassani, A Krause
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
1882016
Gradient methods for submodular maximization
H Hassani, M Soltanolkotabi, A Karbasi
Advances in Neural Information Processing Systems 30, 2017
1552017
Unified scaling of polar codes: Error exponent, scaling exponent, moderate deviations, and error floors
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Information Theory 62 (12), 6698-6712, 2016
1542016
From polar to Reed-Muller codes: A technique to improve the finite-length performance
M Mondelli, SH Hassani, RL Urbanke
IEEE Transactions on Communications 62 (9), 3084-3091, 2014
1532014
On the construction of polar codes
R Pedarsani, SH Hassani, I Tal, E Telatar
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on …, 2011
1512011
Model-based domain generalization
A Robey, GJ Pappas, H Hassani
Advances in Neural Information Processing Systems 34, 20210-20229, 2021
1432021
Stochastic conditional gradient methods: From convex minimization to submodular maximization
A Mokhtari, H Hassani, A Karbasi
Journal of machine learning research 21 (105), 1-49, 2020
1402020
Growing a graph matching from a handful of seeds
E Kazemi, SH Hassani, M Grossglauser
Proceedings of the VLDB Endowment 8 (10), 1010-1021, 2015
1362015
Straggler-resilient federated learning: Leveraging the interplay between statistical accuracy and system heterogeneity
A Reisizadeh, I Tziotis, H Hassani, A Mokhtari, R Pedarsani
IEEE Journal on Selected Areas in Information Theory 3 (2), 197-205, 2022
1342022
Precise tradeoffs in adversarial training for linear regression
A Javanmard, M Soltanolkotabi, H Hassani
Conference on Learning Theory, 2034-2078, 2020
1272020
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Artikler 1–20