Adriano Guastella — accepted AI-conference papers

2026

Sparsity in Federated Learning: A Survey

Alessio Mora, Adriano Guastella, Lorenzo Sani, Paolo Bellavista, Nicholas Lane

IJCAI 2026

Conventional Federated Learning (FL) pipelines focus on the collaborative training of a global dense model across client devices. Sparsity has been increasingly adopted in FL, during or after local optimization, for a range of objectives, including reducing communication and computation costs, suppo

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2025

SparsyFed: Sparse Adaptive Federated Learning

Adriano Guastella, Lorenzo Sani, Alex Iacob, Alessio Mora, Paolo Bellavista, Nicholas Donald Lane

ICLR 2025poster

Sparse training is often adopted in cross-device federated learning (FL) environments where constrained devices collaboratively train a machine learning model on private data by exchanging pseudo-gradients across heterogeneous networks. Although sparse training methods can reduce communication overh…

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