Title
Vertical Federated Learning: Concepts, Advances and Challenges Yang Liu Yan Kang Tianyuan Zou Yanhong Pu Yuanqin He Xiaozhou Ye Ye Ouyang Yaqin Zhang Qian Yang FedML 155 173 0 23 Nov 2022
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges Enrique Tomás Martínez Beltrán Mario Quiles Pérez Pedro Miguel Sánchez Sánchez Sergio López Bernal Gérome Bovet M. Pérez Gregorio Martínez Pérez Alberto Huertas Celdrán FedML 69 254 0 15 Nov 2022
Cross-Silo Federated Learning: Challenges and Opportunities Chao Huang Jianwei Huang Xin Liu FedML 60 61 0 26 Jun 2022
Reconstructing Training Data from Trained Neural Networks Niv Haim Gal Vardi Gilad Yehudai Ohad Shamir Michal Irani 89 141 0 15 Jun 2022
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging Rui Yan Liangqiong Qu Qingyue Wei Shih-Cheng Huang Liyue Shen D. Rubin Lei Xing Yuyin Zhou FedML 141 100 0 17 May 2022
Secure Aggregation for Federated Learning in Flower Kwing Hei Li Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane FedML 73 39 0 12 May 2022
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images Meirui Jiang Zirui Wang Qi Dou FedML 116 130 0 20 Dec 2021
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups A. Wainakh Ephraim Zimmer Sandeep Subedi Jens Keim Tim Grube Shankar Karuppayah Alejandro Sánchez Guinea Max Mühlhäuser 74 9 0 05 Nov 2021
Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources Wentao Li Jiayi Tong M. Anjum N. Mohammed Yong Chen Xiaoqian Jiang FedML 28 10 0 28 Sep 2021
Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease Akis Linardos Kaisar Kushibar S. Walsh P. Gkontra Karim Lekadir FedML 69 68 0 07 Jul 2021
HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning Reza Nasirigerdeh Reihaneh Torkzadehmahani Julian O. Matschinske Jan Baumbach Daniel Rueckert Georgios Kaissis FedML 60 10 0 21 May 2021
OpenFL: An open-source framework for Federated Learning G. A. Reina Alexey Gruzdev Patrick Foley O. Perepelkina Mansi Sharma ... Sarthak Pati Prakash Narayana Moorthy Shih-Han Wang Prashant Shah Spyridon Bakas FedML AIFin 101 112 0 13 May 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 114 440 0 14 Mar 2021
Semi-Supervised Federated Peer Learning for Skin Lesion Classification T. Bdair Nassir Navab Shadi Albarqouni FedML 87 13 0 05 Mar 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 332 874 0 01 Mar 2021
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan Dong Yang Ziyue Xu Wenqi Li Andriy Myronenko H. Roth ... Hitoshi Mori K. Tamura P. An Bradford J. Wood Daguang Xu OOD FedML 88 33 0 23 Nov 2020
Federated Learning for Breast Density Classification: A Real-World Implementation H. Roth Ken Chang Praveer Singh N. Neumark Wenqi Li ... I. Dayan R. Naidu Mona G. Flores D. Rubin Jayashree Kalpathy-Cramer OOD FedML AI4CE 66 166 0 03 Sep 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 140 820 0 28 Jul 2020
Data Poisoning Attacks on Federated Machine Learning Gan Sun Yang Cong Jiahua Dong Qiang Wang Ji Liu FedML AAML 65 207 0 19 Apr 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 121 1,234 0 31 Mar 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 261 1,785 0 18 Mar 2020
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 161 1,008 0 04 Oct 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 153 482 0 28 May 2019
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 85 764 0 01 Apr 2018
Privacy-preserving Prediction Cynthia Dwork Vitaly Feldman 61 91 0 27 Mar 2018
Locally Private Bayesian Inference for Count Models Aaron Schein Zhiwei Steven Wu Alexandra Schofield Mingyuan Zhou Hanna M. Wallach 120 37 0 22 Mar 2018
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 280 4,160 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,172 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,615 0 17 Feb 2016