FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

26 February 2021

Stylianos I. Venieris

Nicholas D. Lane

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Papers citing "FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout"

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Title
FedIN: Federated Intermediate Layers Learning for Model Heterogeneity Yun-Hin Chan Zhihan Jiang Jing Deng Edith C. H. Ngai FedML 26 1 0 03 Apr 2023
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing Sofia Yfantidou Marios Constantinides Dimitris Spathis Athena Vakali Daniele Quercia F. Kawsar HAI FaML 28 18 0 27 Mar 2023
FedGH: Heterogeneous Federated Learning with Generalized Global Header Liping Yi Gang Wang Xiaoguang Liu Zhuan Shi Han Yu FedML 29 71 0 23 Mar 2023
FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning Zheqi Zhu Yuchen Shi Jia Luo Fei-Yue Wang Chenghui Peng Pingyi Fan Khaled B. Letaief FedML 32 20 0 11 Mar 2023
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning Xiaopeng Jiang Cristian Borcea FedML 26 15 0 10 Mar 2023
Memory-adaptive Depth-wise Heterogenous Federated Learning Kai Zhang Yutong Dai Hongyi Wang Eric P. Xing Xun Chen Lichao Sun FedML 28 7 0 08 Mar 2023
FLINT: A Platform for Federated Learning Integration Ewen N. Wang Ajaykumar Kannan Yuefeng Liang Boyi Chen Mosharaf Chowdhury 40 24 0 24 Feb 2023
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving Tianyue Zheng Ang Li Zhe Chen Hao Wang Jun Luo 26 47 0 17 Feb 2023
Federated Learning with Regularized Client Participation Grigory Malinovsky Samuel Horváth Konstantin Burlachenko Peter Richtárik FedML 31 13 0 07 Feb 2023
Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey Jiajun Wu Steve Drew Fan Dong Zhuangdi Zhu Jiayu Zhou FedML 50 46 0 06 Feb 2023
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference Souvik Kundu Shun Lu Yuke Zhang Jacqueline Liu P. Beerel 8 29 0 23 Jan 2023
Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application Liangqi Yuan Lu Su Ziran Wang 33 19 0 12 Jan 2023
Recent Advances on Federated Learning: A Systematic Survey Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 60 78 0 03 Jan 2023
CC-FedAvg: Computationally Customized Federated Averaging Hao Zhang Tingting Wu Siyao Cheng Jie Liu FedML 16 5 0 28 Dec 2022
Federated Learning for Inference at Anytime and Anywhere Zicheng Liu Da Li Javier Fernandez-Marques Stefanos Laskaridis Yan Gao L. Dudziak Stan Z. Li S. Hu Timothy M. Hospedales FedML 26 5 0 08 Dec 2022
PaDPaF: Partial Disentanglement with Partially-Federated GANs Abdulla Jasem Almansoori Samuel Horváth Martin Takáč FedML 23 0 0 07 Dec 2022
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction Samiul Alam Luyang Liu Ming Yan Mi Zhang 28 147 0 03 Dec 2022
Adaptive Compression for Communication-Efficient Distributed Training Maksim Makarenko Elnur Gasanov Rustem Islamov Abdurakhmon Sadiev Peter Richtárik 33 12 0 31 Oct 2022
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout Chen Dun Mirian Hipolito Garcia C. Jermaine Dimitrios Dimitriadis Anastasios Kyrillidis 61 20 0 28 Oct 2022
Exploiting Features and Logits in Heterogeneous Federated Learning Yun-Hin Chan Edith C. H. Ngai FedML 24 2 0 27 Oct 2022
The Future of Consumer Edge-AI Computing Stefanos Laskaridis Stylianos I. Venieris Alexandros Kouris Rui Li Nicholas D. Lane 42 8 0 19 Oct 2022
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs Alexandros Kouris Stylianos I. Venieris Stefanos Laskaridis Nicholas D. Lane 42 8 0 27 Sep 2022
Reducing Impacts of System Heterogeneity in Federated Learning using Weight Update Magnitudes Irene Wang 30 1 0 30 Aug 2022
Federated Learning of Large Models at the Edge via Principal Sub-Model Training Yue Niu Saurav Prakash Souvik Kundu Sunwoo Lee Salman Avestimehr FedML 16 18 0 28 Aug 2022
Lottery Aware Sparsity Hunting: Enabling Federated Learning on Resource-Limited Edge Sara Babakniya Souvik Kundu Saurav Prakash Yue Niu Salman Avestimehr FedML 26 9 0 27 Aug 2022
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning Yuanyuan Chen Zichen Chen Pengcheng Wu Han Yu AI4CE 9 18 0 10 Aug 2022
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity Xinchi Qiu Javier Fernandez-Marques Pedro Gusmão Yan Gao Titouan Parcollet Nicholas D. Lane FedML 50 66 0 04 Aug 2022
FedorAS: Federated Architecture Search under system heterogeneity L. Dudziak Stefanos Laskaridis Javier Fernandez-Marques FedML 31 7 0 22 Jun 2022
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices Kartik Gupta Marios Fournarakis M. Reisser Christos Louizos Markus Nagel FedML 14 14 0 22 Jun 2022
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays Konstantin Mishchenko Francis R. Bach Mathieu Even Blake E. Woodworth 21 57 0 15 Jun 2022
HideNseek: Federated Lottery Ticket via Server-side Pruning and Sign Supermask Anish K. Vallapuram Pengyuan Zhou Young D. Kwon Lik Hang Lee Hengwei Xu Pan Hui 45 10 0 09 Jun 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 9 5 0 07 Jun 2022
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training Rong Dai Li Shen Fengxiang He Xinmei Tian Dacheng Tao FedML 13 111 0 01 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
A Fair Federated Learning Framework With Reinforcement Learning Yaqi Sun Shijing Si Jianzong Wang Yuhan Dong Z. Zhu Jing Xiao FedML 13 7 0 26 May 2022
FedShuffle: Recipes for Better Use of Local Work in Federated Learning Samuel Horváth Maziar Sanjabi Lin Xiao Peter Richtárik Michael G. Rabbat FedML 25 21 0 27 Apr 2022
A Framework for Verifiable and Auditable Federated Anomaly Detection G. Santin Inna Skarbovsky Fabiana Fournier Bruno Lepri FedML 16 1 0 15 Mar 2022
CoCoFL: Communication- and Computation-Aware Federated Learning via Partial NN Freezing and Quantization Kilian Pfeiffer Martin Rapp R. Khalili J. Henkel FedML 13 11 0 10 Mar 2022
FLAME: Federated Learning Across Multi-device Environments Hyunsung Cho Akhil Mathur F. Kawsar 16 21 0 17 Feb 2022
FL_PyTorch: optimization research simulator for federated learning Konstantin Burlachenko Samuel Horváth Peter Richtárik FedML 40 18 0 07 Feb 2022
FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients Jianyu Wang Qi A. S. Rawat Sashank J. Reddi Sagar M. Waghmare Felix X. Yu Gauri Joshi FedML 22 22 0 28 Jan 2022
Minimax Demographic Group Fairness in Federated Learning Afroditi Papadaki Natalia Martínez Martín Bertrán Guillermo Sapiro Miguel R. D. Rodrigues FaML FedML 16 43 0 20 Jan 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients Jaemin Shin Yuanchun Li Yunxin Liu Sung-Ju Lee FedML 17 73 0 05 Jan 2022
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems Martin Rapp R. Khalili Kilian Pfeiffer J. Henkel 19 18 0 16 Dec 2021
SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning Sixing Yu P. Nguyen Waqwoya Abebe Wei Qian Ali Anwar Ali Jannesari FedML 35 20 0 29 Nov 2021
Personalized Federated Learning through Local Memorization Othmane Marfoq Giovanni Neglia Laetitia Kameni Richard Vidal FedML 27 87 0 17 Nov 2021
Towards Fairness-Aware Federated Learning Yuxin Shi Han Yu Cyril Leung FedML 21 79 0 02 Nov 2021
Federated Learning with Heterogeneous Differential Privacy Nasser Aldaghri Hessam Mahdavifar Ahmad Beirami FedML 32 2 0 28 Oct 2021
Efficient and Private Federated Learning with Partially Trainable Networks Hakim Sidahmed Zheng Xu Ankush Garg Yuan Cao Mingqing Chen FedML 49 13 0 06 Oct 2021
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild Mario Almeida Stefanos Laskaridis Abhinav Mehrotra L. Dudziak Ilias Leontiadis Nicholas D. Lane HAI 112 44 0 28 Sep 2021