CVPR 2023 Open Access Repository

2nd Workshop on Federated Learning for Computer Vision

Asynchronous Federated Continual Learning: Donald Shenaj,

Marco Toldo,

Alberto Rigon,

Pietro Zanuttigh; [pdf] [arXiv]
[bibtex]
@InProceedings{Shenaj_2023_CVPR, author = {Shenaj, Donald and Toldo, Marco and Rigon, Alberto and Zanuttigh, Pietro}, title = {Asynchronous Federated Continual Learning}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5055-5063} }
Mixed Quantization Enabled Federated Learning To Tackle Gradient Inversion Attacks: Pretom Roy Ovi,

Emon Dey,

Nirmalya Roy,

Aryya Gangopadhyay; [pdf]
[bibtex]
@InProceedings{Ovi_2023_CVPR, author = {Ovi, Pretom Roy and Dey, Emon and Roy, Nirmalya and Gangopadhyay, Aryya}, title = {Mixed Quantization Enabled Federated Learning To Tackle Gradient Inversion Attacks}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5046-5054} }
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework: Dengsheng Chen,

Vince Junkai Tan,

Zhilin Lu,

Enhua Wu,

Jie Hu; [pdf] [arXiv]
[bibtex]
@InProceedings{Chen_2023_CVPR, author = {Chen, Dengsheng and Tan, Vince Junkai and Lu, Zhilin and Wu, Enhua and Hu, Jie}, title = {OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5018-5026} }
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data: Huancheng Chen,

Haris Vikalo; [pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Chen_2023_CVPR, author = {Chen, Huancheng and Vikalo, Haris}, title = {Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5027-5036} }
TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning With Adaptive Partial Training: Tuo Zhang,

Lei Gao,

Sunwoo Lee,

Mi Zhang,

Salman Avestimehr; [pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Zhang_2023_CVPR, author = {Zhang, Tuo and Gao, Lei and Lee, Sunwoo and Zhang, Mi and Avestimehr, Salman}, title = {TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning With Adaptive Partial Training}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5064-5073} }
Many-Task Federated Learning: A New Problem Setting and a Simple Baseline: Ruisi Cai,

Xiaohan Chen,

Shiwei Liu,

Jayanth Srinivasa,

Myungjin Lee,

Ramana Kompella,

Zhangyang Wang; [pdf] [supp]
[bibtex]
@InProceedings{Cai_2023_CVPR, author = {Cai, Ruisi and Chen, Xiaohan and Liu, Shiwei and Srinivasa, Jayanth and Lee, Myungjin and Kompella, Ramana and Wang, Zhangyang}, title = {Many-Task Federated Learning: A New Problem Setting and a Simple Baseline}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {5037-5045} }