9 citations · 12 across the 5 of their papers we have counts for
6 papers
Dynamic Participation in Federated Learning: Benchmarks and a Knowledge Pool Plugin
Ming-Lun Lee, Fu-Shiang Yang, Cheng-Kuan Lin +3
Federated learning (FL) enables clients to collaboratively train a shared model in a distributed manner, setting it apart from traditional deep learning paradigms. However, most ex…
Zero-Shot Vehicle Model Recognition via Text-Based Retrieval-Augmented Generation
Wei-Chia Chang, Yan-Ann Chen
Vehicle make and model recognition (VMMR) is an important task in intelligent transportation systems, but existing approaches struggle to adapt to newly released models. Contrastiv…
An Adaptive Clustering Scheme for Client Selections in Communication-Efficient Federated Learning
Yan-Ann Chen, Guan-Lin Chen
Federated learning is a novel decentralized learning architecture. During the training process, the client and server must continuously upload and receive model parameters, which c…
FedSAUC: A Similarity-Aware Update Control for Communication-Efficient Federated Learning in Edge Computing
Ming-Lun Lee, Han-Chang Chou, Yan-Ann Chen
Federated learning is a distributed machine learning framework to collaboratively train a global model without uploading privacy-sensitive data onto a centralized server. Usually,…
Semi-Self Representation Learning for Crowdsourced WiFi Trajectories
Yu-Lin Kuo, Yu-Chee Tseng, Ting-Hui Chiang +1
WiFi fingerprint-based localization has been studied intensively. Point-based solutions rely on position annotations of WiFi fingerprints. Trajectory-based solutions, however, requ…
The Privacy Exposure Problem in Mobile Location-based Services
Fang-Jing Wu, Matthias R. Brust, Yan-Ann Chen +1
Mobile location-based services (LBSs) empowered by mobile crowdsourcing provide users with context-aware intelligent services based on user locations. As smartphones are capable of…