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cs.LG2026
Federated Differentially Private Optimization via Low-Rank Preconditioning
Antti Koskela, Tejas Kulkarni, Elias Raninen
We consider differentially private (DP) optimization in the federated setting, where a DP estimate of the feature covariance matrix serves as a Hessian approximation for generalize…
eess.SP2026
EqDeepRx: Learning a Scalable and Interference Mitigating MIMO Receiver
Mikko Honkala, Dani Korpi, Elias Raninen +1
While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from poor scaling with increasing spatial…