block-term

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TheAxeC / covert-vertical-federated-tensor

COVERT: private, communication-efficient vertical federated block-term tensor regression on clinical multi-view data (imaging, ECG, labs), at parity with centralized while transmitting only a DP-noised coupling score.

machine-learning reproducible-research tensor-decomposition differential-privacy federated-learning communication-efficient secure-aggregation vertical-federated-learning clinical-prediction block-term

Updated Jul 7, 2026
Python

TheAxeC / private-coupled-descent

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Private Coupled Descent: dimension-free differential privacy for vertical federated learning by privatizing the small shared coupling variable, with convergence guarantees, matching bounds, and synthetic validation.

privacy reproducible-research optimization theory tensor-decomposition differential-privacy federated-learning vertical-federated-learning convergence-analysis block-term

Updated Jul 4, 2026
Python

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