Knowledge Commons of Institute of Automation,CAS
Federated Learning on Multimodal Data: A Comprehensive Survey | |
Yi-Ming Lin; Yuan Gao; Mao-Guo Gong; Si-Jia Zhang; Yuan-Qiao Zhang; Zhi-Yuan Li | |
发表期刊 | Machine Intelligence Research |
ISSN | 2731-538X |
2023 | |
卷号 | 20期号:4页码:539-553 |
摘要 | With the growing awareness of data privacy, federated learning (FL) has gained increasing attention in recent years as a major paradigm for training models with privacy protection in mind, which allows building models in a collaborative but private way without exchanging data. However, most FL clients are currently unimodal. With the rise of edge computing, various types of sensors and wearable devices generate a large amount of data from different modalities, which has inspired research efforts in multimodal federated learning (MMFL). In this survey, we explore the area of MMFL to address the fundamental challenges of FL on multimodal data. First, we analyse the key motivations for MMFL. Second, the currently proposed MMFL methods are technically classified according to the modality distributions and modality annotations in MMFL. Then, we discuss the datasets and application scenarios of MMFL. Finally, we highlight the limitations and challenges of MMFL and provide insights and methods for future research. |
关键词 | Federated learning, multimodal learning, heterogeneous data, edge computing, collaborative learning |
DOI | 10.1007/s11633-022-1398-0 |
七大方向——子方向分类 | 其他 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
中文导读 | https://mp.weixin.qq.com/s/HgHcbzgz9kvvJp8DEoY3QQ |
视频解析 | https://www.bilibili.com/video/BV1qw4m1d7J4/ |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/55993 |
专题 | 学术期刊_Machine Intelligence Research |
作者单位 | School of Electronic Engineering, Xidian University, Xi′an 710071, China |
推荐引用方式 GB/T 7714 | Yi-Ming Lin, Yuan Gao,Mao-Guo Gong,et al. Federated Learning on Multimodal Data: A Comprehensive Survey[J]. Machine Intelligence Research,2023,20(4):539-553. |
APA | Yi-Ming Lin, Yuan Gao,Mao-Guo Gong,Si-Jia Zhang,Yuan-Qiao Zhang,&Zhi-Yuan Li.(2023).Federated Learning on Multimodal Data: A Comprehensive Survey.Machine Intelligence Research,20(4),539-553. |
MLA | Yi-Ming Lin,et al."Federated Learning on Multimodal Data: A Comprehensive Survey".Machine Intelligence Research 20.4(2023):539-553. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
MIR-2022-08-261.pdf(1253KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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