| Proj No. | A3183-251 |
| Title | Distillation techniques for federated learning |
| Summary | Federated learning allows multiple clients to perform collaborative training without sharing their local datasets with each other. In this framework, information is transmitted from the clients to a server and vice versa. In this project, we study knowledge distillation techniques for federated learning to allow aggregation of information efficiently. This project requires software implementation and familiarity with Python frameworks for deep learning. |
| Supervisor | Prof Tay Wee Peng (Loc:S1 > S1 B1A > S1 B1A 01, Ext: +65 67906280) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Information System Research Lab (Loc: S2-B3a-06) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |