Lai, Phung, Jiang, Xiaopeng, Phan, Hai, Borcea, Cristian, Tran, Khang, Chen, An, Mayyuri, Vijaya Datta, and Jin, Ruoming. FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning. Retrieved from https://par.nsf.gov/biblio/10694513. Web. doi:10.1109/DCOSS-IoT65416.2025.00035.

Lai, Phung, Jiang, Xiaopeng, Phan, Hai, Borcea, Cristian, Tran, Khang, Chen, An, Mayyuri, Vijaya Datta, & Jin, Ruoming. FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning. Retrieved from https://par.nsf.gov/biblio/10694513. https://doi.org/10.1109/DCOSS-IoT65416.2025.00035

Lai, Phung, Jiang, Xiaopeng, Phan, Hai, Borcea, Cristian, Tran, Khang, Chen, An, Mayyuri, Vijaya Datta, and Jin, Ruoming. "FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning". Country unknown/Code not available: The 21st IEEE Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2025). https://doi.org/10.1109/DCOSS-IoT65416.2025.00035. https://par.nsf.gov/biblio/10694513.

@article{osti_10694513,
place = {Country unknown/Code not available}, title = {FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning}, url = {https://par.nsf.gov/biblio/10694513}, DOI = {10.1109/DCOSS-IoT65416.2025.00035}, abstractNote = {Not Available}, journal = {}, publisher = {The 21st IEEE Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2025)}, author = {Lai, Phung and Jiang, Xiaopeng and Phan, Hai and Borcea, Cristian and Tran, Khang and Chen, An and Mayyuri, Vijaya Datta and Jin, Ruoming}, }