Maziar Sanjabi
Maziar Sanjabi
Meta AI
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Cited by
Cited by
Federated Optimization in Heterogeneous Networks
T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smith
arXiv preprint arXiv:1812.06127, 2018
Federated multi-task learning
V Smith, CK Chiang, M Sanjabi, AS Talwalkar
Advances in neural information processing systems 30, 2017
Fair resource allocation in federated learning
T Li, M Sanjabi, A Beirami, V Smith
arXiv preprint arXiv:1905.10497, 2019
Solving a class of non-convex min-max games using iterative first order methods
M Nouiehed, M Sanjabi, T Huang, JD Lee, M Razaviyayn
Advances in Neural Information Processing Systems 32, 2019
Linear Transceiver Design for Interference Alignment: Complexity and Computation
M Razaviyayn, M Sanjabi, ZQ Luo
IEEE Transactions on Information Theory ( Volume: 58 , Issue: 5 , May 2012 …, 2012
Linear transceiver design for interference alignment: Complexity and computation
M Razaviyayn, M Sanjabi Boroujeni, ZQ Luo
Signal Processing Advances in Wireless Communications (SPAWC), 2010 IEEE …, 2010
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
M Sanjabi, B Jimmy, M Razaviyayn, JD Lee
Advances in Neural Information Processing Systems, 7088--7098, 2018
Feddane: A federated newton-type method
T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smithy
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1227-1231, 2019
Tilted empirical risk minimization
T Li, A Beirami, M Sanjabi, V Smith
arXiv preprint arXiv:2007.01162, 2020
A stochastic successive minimization method for nonsmooth nonconvex optimization with applications to transceiver design in wireless communication networks
M Razaviyayn, M Sanjabi, ZQ Luo
Mathematical Programming 157, 515-545, 2016
Robust SINR-constrained MISO downlink beamforming: When is semidefinite programming relaxation tight?
E Song, Q Shi, M Sanjabi, RY Sun, ZQ Luo
EURASIP Journal on Wireless Communications and Networking 2012, 1-11, 2012
Nonconvex min-max optimization: Applications, challenges, and recent theoretical advances
M Razaviyayn, T Huang, S Lu, M Nouiehed, M Sanjabi, M Hong
IEEE Signal Processing Magazine 37 (5), 55-66, 2020
Federated learning with partial model personalization
K Pillutla, K Malik, AR Mohamed, M Rabbat, M Sanjabi, L Xiao
International Conference on Machine Learning, 17716-17758, 2022
Optimal joint base station assignment and beamforming for heterogeneous networks
M Sanjabi, M Razaviyayn, ZQ Luo
IEEE Transactions on Signal Processing 62 (8), 1950-1961, 2014
Accelerated alternating direction method of multipliers
M Kadkhodaie, K Christakopoulou, M Sanjabi, A Banerjee
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
Cross-layer provision of future cellular networks: A WMMSE-based approach
H Baligh, M Hong, WC Liao, ZQ Luo, M Razaviyayn, M Sanjabi, R Sun
IEEE Signal Processing Magazine 31 (6), 56-68, 2014
Where to begin? on the impact of pre-training and initialization in federated learning
J Nguyen, J Wang, K Malik, M Sanjabi, M Rabbat
arXiv preprint arXiv:2210.08090, 2022
A stochastic weighted MMSE approach to sum rate maximization for a MIMO interference channel
M Razaviyayn, MS Boroujeni, ZQ Luo
2013 IEEE 14th Workshop on Signal Processing Advances in Wireless …, 2013
Optimal joint base station assignment and downlink beamforming for heterogeneous networks
M Sanjabi, M Razaviyayn, ZQ Luo
2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012
Solving non-convex non-concave min-max games under polyak-{\L} ojasiewicz condition
M Sanjabi, M Razaviyayn, JD Lee
arXiv preprint arXiv:1812.02878, 2018
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