Client2Vec: Improving Federated Learning by Distribution Shifts Aware
Client Indexing

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing

25 May 2024

Papers citing "Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing"

9 / 9 papers shown

Title
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models Junnan Li Dongxu Li Silvio Savarese Steven C. H. Hoi VLM MLLM 244 4,186 0 30 Jan 2023
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning Yujun Shi Jian Liang Wenqing Zhang Vincent Y. F. Tan Song Bai FedML 64 55 0 01 Oct 2022
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction Yongxin Guo Xiaoying Tang Tao R. Lin FedML 49 27 0 26 May 2022
Test-Time Robust Personalization for Federated Learning Liang Jiang Tao R. Lin FedML OOD TTA 75 41 0 22 May 2022
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 385 4,010 0 28 Jan 2022
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation Yan Shen Jianguo Du Hao Zhang Benyu Zhang Zhanghexuan Ji Mingchen Gao FedML 26 13 0 16 Oct 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 141 287 0 01 May 2021
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 149 9,300 0 28 May 2015
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,150 0 16 Jan 2013