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Harmony: Heterogeneous Multi-Modal Federated Learning through Disentangled Model Training.

, , , , , , , , and . MobiSys, page 530-543. ACM, (2023)

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Optimization Design for Federated Learning in Heterogeneous 6G Networks., , , , , and . IEEE Netw., 37 (2): 38-43 (March 2023)Mozart: A Mobile ToF System for Sensing in the Dark through Phase Manipulation., , , , , and . MobiSys, page 163-176. ACM, (2023)UltraDepth: Exposing High-Resolution Texture from Depth Cameras., , , and . SenSys, page 302-315. ACM, (2021)LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces., and . CoRR, (2024)FedKit: Enabling Cross-Platform Federated Learning for Android and iOS., , , , , , and . CoRR, (2024)HiToF: a ToF camera system for capturing high-resolution textures., , , , , and . MobiCom, page 764-765. ACM, (2022)Design and Deployment of Multi-Modal Federated Learning Systems for Alzheimer's Disease Monitoring.. MobiSys, page 612-614. ACM, (2023)FedDL: Federated Learning via Dynamic Layer Sharing for Human Activity Recognition., , , , and . SenSys, page 15-28. ACM, (2021)ClusterFL: A Clustering-based Federated Learning System for Human Activity Recognition., , , , and . ACM Trans. Sens. Networks, 19 (1): 17:1-17:32 (February 2023)Cosmo: contrastive fusion learning with small data for multimodal human activity recognition., , , , , , and . MobiCom, page 324-337. ACM, (2022)