Seuraa
Gauri Joshi
Gauri Joshi
Carnegie Mellon University
Vahvistettu sähköpostiosoite verkkotunnuksessa andrew.cmu.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Advances and open problems in federated learning
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Foundations and Trends® in Machine Learning 14 (1–2), 1-210, 2021
65372021
Tackling the objective inconsistency problem in heterogeneous federated optimization
J Wang, Q Liu, H Liang, G Joshi, HV Poor
Advances in neural information processing systems 33, 7611-7623, 2020
13982020
Client selection in federated learning: Convergence analysis and power-of-choice selection strategies
YJ Cho, J Wang, G Joshi
arXiv preprint arXiv:2010.01243, 2020
4762020
A Field Guide to Federated Optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ...
arXiv preprint arXiv:2107.06917, 2021
3812021
Cooperative SGD: A unified framework for the design and analysis of communication-efficient SGD algorithms
J Wang, G Joshi
arXiv preprint arXiv:1808.07576, 2018
3392018
Cooperative SGD: A unified framework for the design and analysis of local-update SGD algorithms
J Wang, G Joshi
Journal of Machine Learning Research 22 (213), 1-50, 2021
2982021
Adaptive communication strategies to achieve the best error-runtime trade-off in local-update SGD
J Wang, G Joshi
arXiv preprint arXiv:1810.08313, 2018
2682018
On the delay-storage trade-off in content download from coded distributed storage systems
G Joshi, Y Liu, E Soljanin
IEEE Journal on Selected Areas in Communications 32 (5), 989-997, 2014
2212014
Mariana Raykova, Dawn Song, Weikang Song, Sebastian U
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth …, 2021
2042021
Slow and stale gradients can win the race: Error-runtime trade-offs in distributed SGD
S Dutta, G Joshi, S Ghosh, P Dube, P Nagpurkar
International Conference on Artificial Intelligence and Statistics, 803-812, 2018
2032018
Towards understanding biased client selection in federated learning
YJ Cho, J Wang, G Joshi
International Conference on Artificial Intelligence and Statistics, 10351-10375, 2022
1952022
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
J Wang, AK Sahu, Z Yang, G Joshi, S Kar
arXiv preprint arXiv:1905.09435, 2019
1942019
Using straggler replication to reduce latency in large-scale parallel computing
D Wang, G Joshi, G Wornell
ACM SIGMETRICS Performance Evaluation Review 43 (3), 7-11, 2015
1722015
Efficient redundancy techniques for latency reduction in cloud systems
G Joshi, E Soljanin, G Wornell
ACM Transactions on Modeling and Performance Evaluation of Computing Systems …, 2017
1612017
Efficient task replication for fast response times in parallel computation
D Wang, G Joshi, G Wornell
The 2014 ACM international conference on Measurement and modeling of …, 2014
1432014
Accelerating Deep Learning by Focusing on the Biggest Losers
AH Jiang, DLK Wong, G Zhou, DG Andersen, J Dean, GR Ganger, ...
arXiv preprint arXiv:1910.00762, 2019
1272019
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
YJ Cho, A Manoel, G Joshi, R Sim, D Dimitriadis
arXiv preprint arXiv:2204.12703, 2022
1222022
Adaptive quantization of model updates for communication-efficient federated learning
D Jhunjhunwala, A Gadhikar, G Joshi, YC Eldar
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
1172021
Coding for fast content download
G Joshi, Y Liu, E Soljanin
arXiv preprint arXiv:1210.3012, 2012
1142012
A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning
J Wang, Q Liu, H Liang, G Joshi, HV Poor
IEEE Transactions on Signal Processing 69, 5234-5249, 2021
902021
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Artikkelit 1–20