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Taehong Kim

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Open access Aug 2026

FedVAR: Prototype-aligned federated framework for Video Anomaly Recognition

FedVAR is introduced, a weakly-supervised FL framework explicitly designed for VAR that employs a prototype-based alignment mechanism that creates a shared semantic anchor for all clients to re-center and align their visual and textual feature spaces, establishing a robust framework for distributed intelligence in vide...

Ghani Haider, Majid Kundroo, Boyun Eom et al. · 1 citation
Jul 2026

FedALA-WR: personalized federated learning with adaptive local aggregation and weighted replay

FedALA-WR, a novel framework that integrates adaptive attention-based aggregation with a weighted memory replay mechanism, allowing clients to reinforce valuable past knowledge during local training, consistently outperforms baseline FL and state-of-the-art pFL methods in accuracy and convergence speed.

Tinku Singh, N. Khoa, B. Kumar et al. · 0 citations

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