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Federated learning is widely used to learn intelligent models from decentralized data.
Distilling task-specific knowledge from bert into simple neural networks
Raphael Tang, Yao Lu, Linqing Liu, Lili Mou, Olga Vechtomova, and Jimmy Lin. 2019 · 1903
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Fedmd: Heterogenous federated learning via model distillation
Daliang Li and Junpu Wang. 2019 · 1910
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Embedding-based news recommendation for millions of users
Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima. 2017 · 1942
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Fedner: Medical named entity recognition with federated learning
Suyu Ge, Fangzhao Wu, Chuhan Wu, Tao Qi, Yongfeng Huang, and Xing Xie. 2020 · 2003
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Ensemble distillation for robust model fusion in federated learning
Tao Lin, Lingjing Kong, Sebastian U Stich, and Martin Jaggi. 2020b · 2006
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Federated model distillation with noise-free differential privacy
Lichao Sun and Lingjuan Lyu. 2020 · 2009
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Federated knowledge distillation
Hyowoon Seo, Jihong Park, Seungeun Oh, Mehdi Bennis, and Seong-Lyun Kim. 2020 · 2011
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Adam: A method for stochastic optimization
Yoshua Bengio and Yann LeCun. 2015 · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
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Privacy-preserving deep learning
Reza Shokri and Vitaly Shmatikov. 2015 · 2015
Cited alongside, same era.
Adverse drug reaction classification with deep neural networks
Trung Huynh, Yulan He, Alistair Willis, and Stefan Rueger. 2016 · 2016
Cited alongside, same era.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon. 2016 · 2016
Cited alongside, same era.
Attention-based lstm network for cross-lingual sentiment classification
Xinjie Zhou, Xiaojun Wan, and Jianguo Xiao. 2016 · 2016
Cited alongside, same era.
Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas. 2017 · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Federated topic modeling
Di Jiang, Yuanfeng Song, Yongxin Tong, Xueyang Wu, Weiwei Zhao, Qian Xu, and Qiang Yang. 2019 · 2019
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Kfu nlp team at smm4h 2019 tasks: Want to extract adverse drugs reactions from tweets? bert to the rescue
Zulfat Miftahutdinov, Ilseyar Alimova, and Elena Tutubalina. 2019 · 2019
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Patient knowledge distillation for bert model compression
Siqi Sun, Yu Cheng, Zhe Gan, and Jingjing Liu. 2019 · 2019
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Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2019 · 2019
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Unilmv2: Pseudo-masked language models for unified language model pre-training
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Rohan Anil, Gabriel Pereyra, Alexandre Passos, Robert Ormandi, George E Dahl, and Geoffrey E Hinton. 2018 · 2018
Cited alongside, same era.
Expanding the reach of federated learning by reducing client resource requirements
Sebastian Caldas, Jakub Konečny, H Brendan McMahan, and Ameet Talwalkar. 2018 · 2018
Cited alongside, same era.
Federated learning for mobile keyboard prediction
Andrew Hard, Kanishka Rao, Rajiv Mathews, Swaroop Ramaswamy, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, and Daniel Ramage. 2018 · 2018
Cited alongside, same era.
Dkn: Deep knowledge-aware network for news recommendation
Hongwei Wang, Fuzheng Zhang, Xing Xie, and Minyi Guo. 2018 · 2018
Cited alongside, same era.
Overview of the third social media mining for health (smm4h) shared tasks at emnlp 2018
Davy Weissenbacher, Abeed Sarker, Michael Paul, and Graciela Gonzalez. 2018 · 2018
Cited alongside, same era.
Deep mutual learning
Ying Zhang, Tao Xiang, Timothy M Hospedales, and Huchuan Lu. 2018 · 2018
Cited alongside, same era.
Neural news recommendation with long-and short-term user representations
Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu, and Xing Xie. 2019 · 2019
Cited alongside, same era.
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, et al. 2020 · 2020
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Tinybert: Distilling BERT for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020 · 2020
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Privacy-preserving news recommendation model learning
Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang, and Xing Xie. 2020 · 2020
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Fetchsgd: Communication-efficient federated learning with sketching
Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, and Raman Arora. 2020 · 2020
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Feded: Federated learning via ensemble distillation for medical relation extraction
Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, and Weijian Sun. 2020 · 2020
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Mind: A large-scale dataset for news recommendation
Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, et al. 2020 · 2020
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Deep leakage from gradients
Ligeng Zhu and Song Han. 2020 · 2020
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