Abstract: Federated learning (FL) preserves data privacy by exchanging gradients instead of local training data. However, these private data can still be reconstructed from the exchanged gradients.

Abstract: With increasing concerns on privacy leakage from gradients, various attack mechanisms emerged to recover private data from gradients, which challenged the primary advantage of privacy ...

Introduction: Paste backfilling serves as a key approach for goaf management and mine solid waste disposal. This study investigates the rheological properties of ultra-fine flotation phosphate ...

All gradients can be downloaded and used for free Commercial and non-commercial purposes No permission needed (though attribution is appreciated.) ...