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Recently, semi-supervised federated learning (semi-FL) has been proposed to handle the commonly seen real-world scenarios with labeled data on the server and unlabeled data on the clients.
On the convergence of fedavg on non-iid data
Li, X.; Huang, K.; Yang, W.; Wang, S.; and Zhang, Z. 2019 · 1907
Earlier work this paper cites.
The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Kuznetsova, A.; Rom, H.; Alldrin, N.; Uijlings, J.; Krasin, I.; Pont-Tuset, J.; Kamali, S.; Popov, S.; Malloci, M.; Kolesnikov, A.; et al. 2020 · 1981
Earlier work this paper cites.
Multitask learning
Caruana, R. 1997 · 1997
Earlier work this paper cites.
Adaptive federated optimization
Reddi, S.; Charles, Z.; Zaheer, M.; Garrett, Z.; Rush, K.; Konečnỳ, J.; Kumar, S.; and McMahan, H. B. 2020 · 2003
Earlier work this paper cites.
Support cluster machine
Li, B.; Chi, M.; Fan, J.; and Xue, X. 2007 · 2007
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J.; Weiss, E.; Maheswaranathan, N.; and Ganguli, S. 2015 · 2015
Earlier work this paper cites.
Communication-efficient learning of deep networks from decentralized data
McMahan, B.; Moore, E.; Ramage, D.; Hampson, S.; and y Arcas, B. A. 2017 · 2017
Earlier work this paper cites.
Moment matching for multi-source domain adaptation
Peng, X.; Bai, Q.; Xia, X.; Huang, Z.; Saenko, K.; and Wang, B. 2019 · 2019
Earlier work this paper cites.
Personalized Federated Learning with Moreau Envelopes
Dinh, C. T.; Tran, N. H.; and Nguyen, T. D. 2020 · 2020
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Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach
Fallah, A.; Mokhtari, A.; and Ozdaglar, A. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Earlier work this paper cites.
SCAFFOLD: Stochastic controlled averaging for federated learning
Karimireddy, S. P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A. T. 2020 · 2020
Earlier work this paper cites.
Tackling the objective inconsistency problem in heterogeneous federated optimization
Wang, J.; Liu, Q.; Liang, H.; Joshi, G.; and Poor, H. V. 2020 · 2020
Earlier work this paper cites.
Diffusion models beat gans on image synthesis
Dhariwal, P.; and Nichol, A. 2021 · 2021
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SemiFL: Communication efficient semi-supervised federated learning with unlabeled clients
Diao, E.; Ding, J.; and Tarokh, V. 2021 · 2021
Earlier work this paper cites.
Personalized cross-silo federated learning on non-iid data
Huang, Y.; Chu, L.; Zhou, Z.; Wang, L.; Liu, J.; Pei, J.; and Zhang, Y. 2021 · 2021
Cited alongside, same era.
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Jeong, W.; Yoon, J.; Yang, E.; and Hwang, S. J. 2021 · 2021
Cited alongside, same era.
Advances and open problems in federated learning
Kairouz, P.; McMahan, H. B.; Avent, B.; Bellet, A.; Bennis, M.; Bhagoji, A. N.; Bonawitz, K.; Charles, Z.; Cormode, G.; Cummings, R.; et al. 2021 · 2021
Cited alongside, same era.
Federated learning: Opportunities and challenges
Mammen, P. M. 2021 · 2021
Cited alongside, same era.
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Nichol, A.; Dhariwal, P.; Ramesh, A.; Shyam, P.; Mishkin, P.; McGrew, B.; Sutskever, I.; and Chen, M. 2021 · 2021
Cited alongside, same era.
Deep federated learning for autonomous driving
Nguyen, A.; Do, T.; Tran, M.; Nguyen, B. X.; Duong, C.; Phan, T.; Tjiputra, E.; and Tran, Q. D. 2022 · 2022
Later among the works it cites.
Diffusion autoencoders: Toward a meaningful and decodable representation
Preechakul, K.; Chatthee, N.; Wizadwongsa, S.; and Suwajanakorn, S. 2022 · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
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Palette: Image-to-image diffusion models
Saharia, C.; Chan, W.; Chang, H.; Lee, C.; Ho, J.; Salimans, T.; Fleet, D.; and Norouzi, M. 2022a · 2022
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Pretraining is all you need for image-to-image translation
Wang, T.; Zhang, T.; Zhang, B.; Ouyang, H.; Chen, D.; Chen, Q.; and Wen, F. 2022 · 2022
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Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
Cited alongside, same era.
Personalized Federated Learning with First Order Model Optimization
Zhang, M.; Sapra, K.; Fidler, S.; Yeung, S.; and Alvarez, J. M. 2021a · 2021
Cited alongside, same era.
Improving semi-supervised federated learning by reducing the gradient diversity of models
Zhang, Z.; Yang, Y.; Yao, Z.; Yan, Y.; Gonzalez, J. E.; Ramchandran, K.; and Mahoney, M. W. 2021b · 2021
Cited alongside, same era.
Feddrive: Generalizing federated learning to semantic segmentation in autonomous driving
Fantauzzo, L.; Fanì, E.; Caldarola, D.; Tavera, A.; Cermelli, F.; Ciccone, M.; and Caputo, B. 2022 · 2022
Cited alongside, same era.
Guo, T.; Guo, S.; Wang, J.; and Xu, W. 2022 · 2022
Cited alongside, same era.
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity
Heinbaugh, C. E.; Luz-Ricca, E.; and Shao, H. 2022 · 2022
Cited alongside, same era.
Diffusionclip: Text-guided diffusion models for robust image manipulation
Kim, G.; Kwon, T.; and Ye, J. C. 2022 · 2022
Cited alongside, same era.
Du, Y.; Durkan, C.; Strudel, R.; Tenenbaum, J. B.; Dieleman, S.; Fergus, R.; Sohl-Dickstein, J.; Doucet, A.; and Grathwohl, W. 2023 · 2023
Closest in time.
Composer: Creative and controllable image synthesis with composable conditions
Huang, L.; Chen, D.; Liu, Y.; Shen, Y.; Zhao, D.; and Zhou, J. 2023 · 2023
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Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis
Jin, Z.; Shen, X.; Li, B.; and Xue, X. 2023 · 2023
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Kirillov, A.; Mintun, E.; Ravi, N.; Mao, H.; Rolland, C.; Gustafson, L.; Xiao, T.; Whitehead, S.; Berg, A. C.; Lo, W.-Y.; et al. 2023 · 2023
Closest in time.
Shao, J.; Li, Z.; Sun, W.; Zhou, T.; Sun, Y.; Liu, L.; Lin, Z.; and Zhang, J. 2023 · 2023
Closest in time.
One-shot Federated Learning without server-side training
Su, S.; Li, B.; and Xue, X. 2023 · 2023
Closest in time.
One-Shot Federated Learning with Classifier-Guided Diffusion Models
Yang, M.; Su, S.; Li, B.; and Xue, X. 2023 · 2023
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Chinese Text Recognition with A Pre-Trained CLIP-Like Model Through Image-IDS Aligning
Yu, H.; Wang, X.; Li, B.; and Xue, X. 2023 · 2023
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Adding conditional control to text-to-image diffusion models
Zhang, L.; and Agrawala, M. 2023 · 2023
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