Feddat: An approach for foundation model finetuning in multi-modal heterogeneous federated learning
Recently, foundation models have exhibited remarkable advancements in multi-modal
learning. These models, equipped with millions (or billions) of parameters, typically require a …
learning. These models, equipped with millions (or billions) of parameters, typically require a …
Unlocking the potential of prompt-tuning in bridging generalized and personalized federated learning
Abstract Vision Transformers (ViT) and Visual Prompt Tuning (VPT) achieve state-of-the-art
performance with improved efficiency in various computer vision tasks. This suggests a …
performance with improved efficiency in various computer vision tasks. This suggests a …
Advances and open challenges in federated learning with foundation models
The integration of Foundation Models (FMs) with Federated Learning (FL) presents a
transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …
transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …
Language-Guided Transformer for Federated Multi-Label Classification
Federated Learning (FL) is an emerging paradigm that enables multiple users to
collaboratively train a robust model in a privacy-preserving manner without sharing their …
collaboratively train a robust model in a privacy-preserving manner without sharing their …
[PDF][PDF] 語言引導之變換器於聯邦式多標籤分類
劉亦傑 - 2024 - tdr.lib.ntu.edu.tw
摘要聯邦學習(FL) 是一種新興的模型學習框架, 該方法使多個用戶能夠在不共享私人數據的情況
下協作訓練一個強大的模型, 以保護隱私. 大多數現有的FL 方法僅考慮傳統的單標籤圖像分類 …
下協作訓練一個強大的模型, 以保護隱私. 大多數現有的FL 方法僅考慮傳統的單標籤圖像分類 …