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Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative training.
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Discovering optimal variable-length time series motifs in large-scale wearable recordings of human bio-behavioral signals. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 7615–7619
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FedML: A Research Library and Benchmark for Federated Machine Learning
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Federated optimization in heterogeneous networks
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Ensemble distillation for robust model fusion in federated learning
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Fednlp: Benchmarking federated learning methods for natural language processing tasks
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Mobilevit: light-weight, general-purpose, and mobile-friendly vision transformer
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Privacy in deep learning: A survey
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, and Hadi Esmaeilzadeh. 2020 · 2020
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Training strategies to handle missing modalities for audio-visual expression recognition. In Companion Publication of the 2020 International Conference on Multimodal Interaction . 400–404
Srinivas Parthasarathy and Shiva Sundaram. 2020 · 2020
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Adaptive federated optimization
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Federated self-supervised learning of multisensor representations for embedded intelligence
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Deep learning for ECG analysis: Benchmarks and insights from PTB-XL
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Mobilebert: a compact task-agnostic bert for resource-limited devices
Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, and Denny Zhou. 2020 · 2020
Cited alongside, same era.
PTB-XL, a large publicly available electrocardiography dataset
Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I Lunze, Wojciech Samek, and Tobias Schaeffter. 2020 · 2020
Cited alongside, same era.
Confident learning: Estimating uncertainty in dataset labels
Curtis Northcutt, Lu Jiang, and Isaac Chuang. 2021 · 2021
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A federated learning aggregation algorithm for pervasive computing: Evaluation and comparison. In 2021 IEEE International Conference on Pervasive Computing and Communications (PerCom) . IEEE, 1–10
EK Sannara, Francois Portet, Philippe Lalanda, and VEGA German. 2021 · 2021
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KU-HAR: An open dataset for heterogeneous human activity recognition
Niloy Sikder and Abdullah-Al Nahid. 2021 · 2021
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Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities
Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, and Salman Avestimehr. 2021a · 2021
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Improving semi-supervised federated learning by reducing the gradient diversity of models. In 2021 IEEE International Conference on Big Data (Big Data) . IEEE, 1214–1225
Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E Gonzalez, Kannan Ramchandran, and Michael W Mahoney. 2021b · 2021
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Collaborative unsupervised visual representation learning from decentralized data. In Proceedings of the IEEE/CVF international conference on computer vision . 4912–4921
Weiming Zhuang, Xin Gan, Yonggang Wen, Shuai Zhang, and Shuai Yi. 2021 · 2021
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The field of human building interaction for convergent research and innovation for intelligent built environments
Burçin Becerik-Gerber, Gale M. Lucas, Ashrant Aryal, Mohamad Awada, Mario Bergés, Sarah Billington, Olga Boric-Lubecke, Ali Ghahramani, Arsalan Heydarian, Christoph Höelscher, Farrokh Jazizadeh, Azam Khan, Jared Langevin, Ruying Liu, Frederick Marks, Matthew Louis Mauriello, Elizabeth L. Murnane, Haeyoung Noh, Marco Pritoni, Shawn C Roll, Davide Schaumann, Mir Hasan Seyedrezaei, John Ellor Taylor, Jie Zhao, and Runhe Zhu. 2022 · 2022
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FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 87–96
Jiayi Chen and Aidong Zhang. 2022 · 2022
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Heterogeneous ensemble knowledge transfer for training large models in federated learning
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, and Dimitrios Dimitriadis. 2022 · 2022
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Flute: A scalable, extensible framework for high-performance federated learning simulations
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal Diaz, Andre Manoel, and Robert Sim. 2022 · 2022
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Tiantian Feng and Shrikanth Narayanan. 2022 · 2022
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User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition on Federated Learning. In Proc. Interspeech 2022 . 5055–5059
Tiantian Feng, Raghuveer Peri, and Shrikanth Narayanan. 2022 · 2022
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Label inference attacks against vertical federated learning. In 31st USENIX Security Symposium (USENIX Security 22) . 1397–1414
Chong Fu, Xuhong Zhang, Shouling Ji, Jinyin Chen, Jingzheng Wu, Shanqing Guo, Jun Zhou, Alex X Liu, and Ting Wang. 2022 · 2022
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Ego4d: Around the world in 3,000 hours of egocentric video. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 18995–19012
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
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Fedcvt: Semi-supervised vertical federated learning with cross-view training
Yan Kang, Yang Liu, and Xinle Liang. 2022 · 2022
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FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, et al · 2022
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Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) . IEEE, 359–364
Vasileios Tsouvalas, Tanir Ozcelebi, and Nirvana Meratnia. 2022 · 2022
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FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, and Jingren Zhou. 2022 · 2022
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FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing
Yuexiang Xie, Zhen Wang, Daoyuan Chen, Dawei Gao, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, and Jingren Zhou. 2022 · 2022
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A unified framework for multi-modal federated learning
Baochen Xiong, Xiaoshan Yang, Fan Qi, and Changsheng Xu. 2022 · 2022
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FedAudio: A Federated Learning Benchmark for Audio Tasks
Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S Narayanan, and Salman Avestimehr. 2022 · 2022
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A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness
Tiantian Feng, Rajat Hebbar, Nicholas Mehlman, Xuan Shi, Aditya Kommineni, and Shrikanth Narayanan. 2023 · 2023
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Secure Federated Learning against Model Poisoning Attacks via Client Filtering
Duygu Yaldiz, Tuo Zhang, and Salman Avestimehr. 2023 · 2023
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Multimodal Federated Learning via Contrastive Representation Ensemble. In International Conference on Learning Representations
Qiying Yu, Yimu Wang, Ke Xu, Yang Liu, and Jingjing Liu. 2023 · 2023
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