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M A U Shariff

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#federated learning Open access Sep 2026

mhnarfth/who-benefits-federation: INDIS 2026 camera-ready

Software archive accompanying the paper "Who Benefits from Federation? Heterogeneous Gains in Cross-Operator Network Traffic Representation Learning" by Mohammad Arafath Uddin Shariff and Byrav Ramamurthy (School of Computing, University of Nebraska-Lincoln), presented at the 13th International Workshop on Innovating t...

M A U Shariff · 0 citations
#federated learning Open access Sep 2026

mhnarfth/who-benefits-federation: INDIS 2026 camera-ready

Software archive accompanying the paper "Who Benefits from Federation? Heterogeneous Gains in Cross-Operator Network Traffic Representation Learning" by Mohammad Arafath Uddin Shariff and Byrav Ramamurthy (School of Computing, University of Nebraska-Lincoln), presented at the 13th International Workshop on Innovating t...

M A U Shariff · 0 citations

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