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One-shot Federated Learning (OFL) has become a promising learning paradigm, enabling the training of a global server model via a single communication round.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Modeldb: a system for machine learning model management
Manasi Vartak, Harihar Subramanyam, Wei-En Lee, Srinidhi Viswanathan, Saadiyah Husnoo, Samuel Madden, and Matei Zaharia · 2016
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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
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Shufflenet v2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 2018
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Deep co-training for semi-supervised image recognition
Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo Wang, and Alan Yuille · 2018
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Data-free learning of student networks
Hanting Chen, Yunhe Wang, Chang Xu, Zhaohui Yang, Chuanjian Liu, Boxin Shi, Chunjing Xu, Chao Xu, and Qi Tian · 2019
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Neel Guha, Ameet Talwalkar, and Virginia Smith · 2019
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Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, et al · 2019
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Gradient harmonized single-stage detector
Buyu Li, Yu Liu, and Xiaogang Wang · 2019
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Ppgan: Privacy-preserving generative adversarial network
Yi Liu, Jialiang Peng, JQ James, and Yi Wu · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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What can be transferred: Unsupervised domain adaptation for endoscopic lesions segmentation
Jiahua Dong, Yang Cong, Gan Sun, Bineng Zhong, and Xiaowei Xu · 2020
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Scaffold: Stochastic controlled averaging for federated learning
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian Stich, and Ananda Theertha Suresh · 2020
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Ensemble distillation for robust model fusion in federated learning
See through gradients: Image batch recovery via gradinversion
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M Alvarez, Jan Kautz, and Pavlo Molchanov · 2021
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Data-free knowledge distillation for heterogeneous federated learning
Zhuangdi Zhu, Junyuan Hong, and Jiayu Zhou · 2021
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Improving generalization in federated learning by seeking flat minima
Debora Caldarola, Barbara Caputo, and Marco Ciccone · 2022
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On the importance and applicability of pre-training for federated learning
Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, and Wei-Lun Chao · 2022
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Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training
Rong Dai, Li Shen, Fengxiang He, Xinmei Tian, and Dacheng Tao · 2022
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Generalized federated learning via sharpness aware minimization
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Tao Lin, Lingjing Kong, Sebastian U Stich, and Martin Jaggi · 2020
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Diversity can be transferred: Output diversification for white-and black-box attacks
Yusuke Tashiro, Yang Song, and Stefano Ermon · 2020
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Man-in-the-middle attacks against machine learning classifiers via malicious generative models
Derui Wang, Chaoran Li, Sheng Wen, Surya Nepal, and Yang Xiang · 2020
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Tackling the objective inconsistency problem in heterogeneous federated optimization
Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, and H Vincent Poor · 2020
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Dreaming to distill: Data-free knowledge transfer via deepinversion
Hongxu Yin, Pavlo Molchanov, Jose M Alvarez, Zhizhong Li, Arun Mallya, Derek Hoiem, Niraj K Jha, and Jan Kautz · 2020
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Distilled one-shot federated learning
Yanlin Zhou, George Pu, Xiyao Ma, Xiaolin Li, and Dapeng Wu · 2020
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Federated learning based on dynamic regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, and Venkatesh Saligrama · 2021
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Zhe Qu, Xingyu Li, Rui Duan, Yao Liu, Bo Tang, and Zhuo Lu · 2022
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Virtual homogeneity learning: Defending against data heterogeneity in federated learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, and Xiaowen Chu · 2022
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Video moment retrieval with cross-modal neural architecture search
Xun Yang, Shanshan Wang, Jian Dong, Jianfeng Dong, Meng Wang, and Tat-Seng Chua · 2022
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Fedgamma: Federated learning with global sharpness-aware minimization
Rong Dai, Xun Yang, Yan Sun, Li Shen, Xinmei Tian, Meng Wang, and Yongdong Zhang · 2023
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Towards addressing label skews in one-shot federated learning
Yiqun Diao, Qinbin Li, and Bingsheng He · 2023
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Data-free one-shot federated learning under very high statistical heterogeneity
Clare Elizabeth Heinbaugh, Emilio Luz-Ricca, and Huajie Shao · 2023
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Sade: A self-adaptive expert for multi-dataset question answering
Yixing Peng, Quan Wang, Zhendong Mao, and Yongdong Zhang · 2023
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Emotion-prior awareness network for emotional video captioning
Peipei Song, Dan Guo, Xun Yang, Shengeng Tang, Erkun Yang, and Meng Wang · 2023
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Dafkd: Domain-aware federated knowledge distillation
Haozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, and Zhigang Zeng · 2023
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Exploring one-shot semi-supervised federated learning with a pre-trained diffusion model
Mingzhao Yang, Shangchao Su, Bin Li, and Xiangyang Xue · 2023
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Federated domain generalization with generalization adjustment
Ruipeng Zhang, Qinwei Xu, Jiangchao Yao, Ya Zhang, Qi Tian, and Yanfeng Wang · 2023
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Exploring sparse spatial relation in graph inference for text-based vqa
Sheng Zhou, Dan Guo, Jia Li, Xun Yang, and Meng Wang · 2023
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When foundation model meets federated learning: Motivations, challenges, and future directions
Weiming Zhuang, Chen Chen, and Lingjuan Lyu · 2023
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