activity
20242026
collaborators

21 papers

quant-ph2026

Optimal Calibration of Quantum Network Links

Vinay Kumar, Claudio Cicconetti, Marco Conti +1

The reliable distribution of entanglement is essential for the effective operation of quantum networks. Due to fundamental differences between quantum and classical communication s…

cs.SI2026

Annotation of Positive vs Negative User Interactions for Social Sign Prediction

Biancamaria Bombino, Chiara Boldrini, Andrea Passarella +1

Inferring the sign of social relationships from online interactions is a fundamental challenge in social network analysis. Existing approaches typically rely on sentiment analysis…

cs.NI2026

Operating Regimes of Decentralized Learning Under Mobility and Bandwidth Constraints

Samuele Sabella, Chiara Boldrini, Lorenzo Valerio +2

Decentralized learning is a promising paradigm for collaborative training in mobile and pervasive systems, as it avoids a central coordinator and does not require sharing raw data.…

cs.SI2026

Layered Ego Networks in Email Communication: From Enron to the Jmail Archive

Francesco Di Cursi, Chiara Boldrini, Marco Conti +1

Email archives offer a rare view of social relationships through repeated communication, but it remains unclear how well classical ego network layering applies to digital interacti…

cs.LG2026

Neural Network Compression by Approximate Differential Equivalence

Ravi Dhiman, Andrea Passarella, Mirco Tribastone +1

Neural network compression is commonly achieved by pruning parameters based on local importance scores, e.g., magnitude-based pruning. We propose a complementary approach that comp…

cs.LG2026

FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher

Alessio Mora, Lorenzo Valerio, Paolo Bellavista +1

Federated Learning (FL) enables the collaborative training of machine learning models without requiring centralized collection of user data. To comply with the right to be forgotte…