Federated Learning with Only Positive Labels by Exploring Label Correlations

24 April 2024

Li Shen

Bo Du

Papers citing "Federated Learning with Only Positive Labels by Exploring Label Correlations"

21 / 21 papers shown

Title
FLAG: Fast Label-Adaptive Aggregation for Multi-label Classification in Federated Learning Shih-Fang Chang Benny Wei-Yun Hsu Tien-Yu Chang Vincent S. Tseng 42 2 0 27 Feb 2023
ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond Qiming Zhang Yufei Xu Jing Zhang Dacheng Tao ViT 71 233 0 21 Feb 2022
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT Zonghang Li Yihong He Hongfang Yu Jiawen Kang Xiaoping Li Zenglin Xu Dusit Niyato FedML 99 97 0 03 Feb 2022
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias Yufei Xu Qiming Zhang Jing Zhang Dacheng Tao ViT 138 336 0 07 Jun 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 75 655 0 20 May 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 52 192 0 12 May 2021
Personalized Federated Learning using Hypernetworks Aviv Shamsian Aviv Navon Ethan Fetaya Gal Chechik FedML 108 332 0 08 Mar 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 307 865 0 01 Mar 2021
The Emerging Trends of Multi-Label Learning Weiwei Liu Haobo Wang Xiaobo Shen Ivor W. Tsang 72 262 0 23 Nov 2020
Ternary Compression for Communication-Efficient Federated Learning Jinjin Xu W. Du Ran Cheng Wangli He Yaochu Jin MQ FedML 61 179 0 07 Mar 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization Zhize Li D. Kovalev Xun Qian Peter Richtárik FedML AI4CE 91 137 0 26 Feb 2020
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 135 1,143 0 13 Sep 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 89 998 0 23 Jul 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 52 405 0 06 Jun 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 61 1,353 0 07 Mar 2019
Federated Heavy Hitters Discovery with Differential Privacy Wennan Zhu Peter Kairouz H. B. McMahan Haicheng Sun Wei Li FedML 66 109 0 22 Feb 2019
Automated Latent Fingerprint Recognition Kai Cao Anil K. Jain 47 177 0 06 Apr 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 286 4,636 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 189 6,109 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 380 17,437 0 17 Feb 2016
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 371 43,524 0 01 May 2014