3 papers
cs.LG2026
ERIS: Enhancing Privacy and Scalability in Federated Learning via Federated Shard Aggregation
Dario Fenoglio, Pasquale Polverino, Jacopo Quizi +3
Scaling Federated Learning (FL) to billion-parameter models forces a challenging trade-off between privacy, scalability, and model utility. Existing solutions often tackle these ch…
math.NA2026
Samplet limits and multiwavelets
Gianluca Giacchi, Michael Multerer, Jacopo Quizi
Samplets are data adapted multiresolution analyses of localized discrete signed measures. They can be constructed on scattered data sites in arbitrary dimension such that they exhi…
eess.SP2025
Bespoke multiresolution analysis of graph signals
Giacomo Elefante, Gianluca Giacchi, Michael Multerer +1
We present a novel framework for discrete multiresolution analysis of graph signals. The main analytical tool is the samplet transform, originally defined in the Euclidean framewor…