Yi Zhou
Yi Zhou
Research Staff Member, IBM Research
Zweryfikowany adres z ibm.com
Tytuł
Cytowane przez
Cytowane przez
Rok
An optimal randomized incremental gradient method
G Lan, Y Zhou
Mathematical programming, 1-49, 2017
1982017
A hybrid approach to privacy-preserving federated learning
S Truex, N Baracaldo, A Anwar, T Steinke, H Ludwig, R Zhang, Y Zhou
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
1922019
Communication-efficient algorithms for decentralized and stochastic optimization
G Lan, S Lee, Y Zhou
Mathematical Programming, 1-48, 2017
1672017
Conditional gradient sliding for convex optimization
G Lan, Y Zhou
SIAM Journal on Optimization 26 (2), 1379-1409, 2016
1262016
Hybridalpha: An efficient approach for privacy-preserving federated learning
R Xu, N Baracaldo, Y Zhou, A Anwar, H Ludwig
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
632019
A unified variance-reduced accelerated gradient method for convex optimization
G Lan, Z Li, Y Zhou
arXiv preprint arXiv:1905.12412, 2019
382019
Random gradient extrapolation for distributed and stochastic optimization
G Lan, Y Zhou
SIAM Journal on Optimization 28 (4), 2753-2782, 2018
362018
Conditional accelerated lazy stochastic gradient descent
G Lan, S Pokutta, Y Zhou, D Zink
International Conference on Machine Learning, 1965-1974, 2017
322017
Tifl: A tier-based federated learning system
Z Chai, A Ali, S Zawad, S Truex, A Anwar, N Baracaldo, Y Zhou, H Ludwig, ...
Proceedings of the 29th International Symposium on High-Performance Parallel …, 2020
292020
Towards Taming the Resource and Data Heterogeneity in Federated Learning
Z Chai, H Fayyaz, Z Fayyaz, A Anwar, Y Zhou, N Baracaldo, H Ludwig, ...
2019 {USENIX} Conference on Operational Machine Learning (OpML 19), 19-21, 2019
242019
IBM Federated Learning: an Enterprise Framework White Paper V0. 1
H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ...
arXiv preprint arXiv:2007.10987, 2020
192020
Asynchronous decentralized accelerated stochastic gradient descent
G Lan, Y Zhou
IEEE Journal on Selected Areas in Information Theory 2 (2), 802-811, 2021
62021
Mitigating Bias in Federated Learning
A Abay, Y Zhou, N Baracaldo, S Rajamoni, E Chuba, H Ludwig
arXiv preprint arXiv:2012.02447, 2020
22020
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
R Xu, N Baracaldo, Y Zhou, A Anwar, J Joshi, H Ludwig
arXiv preprint arXiv:2103.03918, 2021
12021
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
S Zawad, A Ali, PY Chen, A Anwar, Y Zhou, N Baracaldo, Y Tian, F Yan
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10807 …, 2021
12021
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
K Varma, Y Zhou, N Baracaldo, A Anwar
arXiv preprint arXiv:2107.12490, 2021
2021
Graph topology invariant gradient and sampling complexity for decentralized and stochastic optimization
G Lan, Y Ouyang, Y Zhou
arXiv preprint arXiv:2101.00143, 2021
2021
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