7 citations · 7 across the 3 of their papers we have counts for
3 papers
Verifiable Split Learning via zk-SNARKs
Rana Alaa, Darío González-Ferreiro, Carlos Beis-Penedo +3
Split learning is an approach to collaborative learning in which a deep neural network is divided into two parts: client-side and server-side at a cut layer. The client side execut…
Privacy-aware Berrut Approximated Coded Computing applied to general distributed learning
Xavier Martínez-Luaña, Manuel Fernández-Veiga, Rebeca P. Díaz-Redondo +1
Coded computing is one of the techniques that can be used for privacy protection in Federated Learning. However, most of the constructions used for coded computing work only under…
Simulation of fidelity in entanglement-based networks with repeater chains
David Pérez Castro, Ana Fernández Vilas, Manuel Fernández-Veiga +2
We implement a simulation environment on top of NetSquid that is specifically designed for estimating the end-to-end fidelity across a path of quantum repeaters or quantum switches…