Artificial Intelligence-Driven Multimodal Sensor Fusion for Complex Market Systems via Federated Transformer-Based Learning
Lei Shi, Mingran Tian, Yinfei Yi, Xinyi Hu, Xiaoya Wang, Yating Yang, Manzhou Li · 2026
Read Artificial Intelligence-Driven Multimodal Sensor Fusion for Complex Market Systems via Federated Transformer-Based Learning by Lei Shi, Mingran Tian, Yinfei Yi, Xinyi Hu, Xiaoya Wang, Yating Yang, Manzhou Li (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13120609.txt.
Description
In highly digitalized and networked modern trading systems, large volumes of heterogeneous data are continuously generated from multiple sources during market operations. However, due to the complexity of data structures, significant differences in temporal scales, and constraints imposed by data privacy protection, traditional single-source modeling approaches are unable to fully exploit multisource information.
Catalog record
| CREATOR | Lei Shi, Mingran Tian, Yinfei Yi, Xinyi Hu, Xiaoya Wang, Yating Yang, Manzhou Li |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 81 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |