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Federated learning (FL) hyper-parameters significantly affect the training overheads in terms of computation time, transmission time, computation load, and transmission load.
Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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Practical Bayesian Optimization of Machine Learning Algorithms
J. Snoek, H. Larochelle, and R. P. Adams · 2012
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Almost Optimal Exploration in Multi-Armed Bandits
Z. Karnin, T. Koren, and O. Somekh · 2013
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Machine Learning: Trends, Perspectives, and Prospects
M. I. Jordan and T. M. Mitchell · 2015
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Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Emnist: Extending mnist to handwritten letters
G. Cohen, S. Afshar, J. Tapson, and A. van Schaik · 2017
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Hyperband: A Novel Bandit-based Approach to Hyperparameter Optimization
L. Li, K. Jamieson, G. DeSalvo, A. Rostamizadeh, and A. Talwalkar · 2017
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Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan, D. R. Eider Moore, S. Hampson, and B. A. Arcas · 2017
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Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
P. Warden · 2018
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Federated Learning for Mobile Keyboard Prediction
A. Hard, K. Rao, R. Mathews, S. Ramaswamy, F. Beaufays, S. Augenstein, H. Eichner, C. Kiddon, and D. Ramage · 2019
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Federated Optimization in Heterogeneous Networks
T. Li, A. K. Sahu, M. Zaheer, M. Sanjabi, A. Talwalkar, and V. Smith · 2020
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On the Convergence of FedAvg on Non-IID Data
X. Li, K. Huang, W. Yang, S. Wang, and Z. Zhang · 2020
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A Survey on Distributed Machine Learning
J. Verbraeken, M. Wolting, J. Katzy, J. Kloppenburg, T. Verbelen, and J. S. Rellermeyer · 2020
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Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
J. Wang, Q. Liu, H. Liang, G. Joshi, and H. Vincent Poor · 2020
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Intelligent Traffic Monitoring Systems for Vehicle Classification: A Survey
M. Won · 2020
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On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice
L. Yang and A. Shami · 2020
Oort: Efficient Federated Learning via Guided Participant Selection
F. Lai, X. Zhu, H. V. Madhyastha, and M. Chowdhury · 2021
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Smart Home Reasoning Systems: A Systematic Literature Review
D. N. Mekuria, P. Sernani, N. Falcionelli, and A. F. Dragoni · 2021
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Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
M. Paulik, M. Seigel, H. Mason, D. Telaar, J. Kluivers, R. van Dalen, C. W. Lau, L. Carlson, F. Granqvist, C. Vandevelde, S. Agarwal, J. Freudiger, A. Byde, A. Bhowmick, G. Kapoor, S. Beaumont, A. Cahill, D. Hughes, O. Javidbakht, F. Dong, R. Rishi, and S. Hung · 2021
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Adaptive federated optimization
S. J. Reddi, Z. Charles, M. Zaheer, Z. Garrett, K. Rush, J. Konecny, S. Kumar, and H. B. McMahan · 2021
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A Field Guide to Federated Optimization
J. Wang, Z. Charles, Z. Xu, G. Joshi, H. B. McMahan, B. A. y. Arcas, M. Al-Shedivat, G. Andrew, S. Avestimehr, K. Daly, D. Data, S. Diggavi, H. Eichner, A. Gadhikar, Z. Garrett, A. M. Girgis, F. Hanzely, A. Hard, C. He, S. Horvath, Z. Huo, A. Ingerman, M. Jaggi, T. Javidi, P. Kairouz, S. Kale, S. P. Karimireddy, J. Konecny, and etc · 2021
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Deep Learning in the Era of Edge Computing: Challenges and Opportunities
M. Zhang, F. Zhang, N. Lane, Y. Shu, X. Zeng, B. Fang, S. Yan, and H. Xu · 2020
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Attack and Anomaly Detection in IoT Networks using Machine Learning Techniques: A Review
S. H. Haji and S. Y. Ameen · 2021
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Federated hyperparameter tuning: Challenges, baselines, and connections to weight-sharing
M. Khodak, R. Tu, T. Li, L. Li, M.-F. Balcan, V. Smith, and A. Talwalkar · 2021
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FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
Y. Zhou, P. Ram, T. Salonidis, N. Baracaldo, H. Samulowitz, and H. Ludwig · 2021
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FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
S. Alam, L. Liu, M. Yan, and M. Zhang · 2022
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PyramidFL: A Fine-grained Client Selection Framework for Efficient Federated Learning
C. Li, X. Zeng, M. Zhang, and Z. Cao · 2022
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Federated learning for internet of things: Applications, challenges, and opportunities
T. Zhang, L. Gao, C. He, M. Zhang, B. Krishnamachari, and S. Avestimehr · 2022
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