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cs.LG2026
Latent Information Sharing for Accelerating Federated Learning
Seungjun Lee, Ensieh Khazaei, Dimitrios Hatzinakos +2
Federated learning (FL) is a communication-efficient distributed learning paradigm. However, client drift remains one of the most critical challenges, hindering the efficient train…
cs.LG2026
Omni-modal decomposition autoencoders learn full-stack wearable disentangled representations
Ioannis Ziogas, Ensieh Khazaei, Bilal Taha +4
Learning disentangled representations is a key requirement for developing versatile, general-purpose, and sustainable models in multi-modal wearable computing. However, existing ap…
cs.LG2024
CDFL: Efficient Federated Human Activity Recognition using Contrastive Learning and Deep Clustering
Ensieh Khazaei, Alireza Esmaeilzehi, Bilal Taha +1
In the realm of ubiquitous computing, Human Activity Recognition (HAR) is vital for the automation and intelligent identification of human actions through data from diverse sensors…