publications

2026

1. arXiv

   Empty SPACE: Cross-Attention Sparsity for Concept Erasure in Diffusion Models

   Nicola Novello and Andrea M Tonello

   arXiv preprint arXiv:2605.10198, 2026
2. ICML

   

   A Unified Framework for Diffusion Model Unlearning with f-Divergence

   Nicola Novello, Federico Fontana, Luigi Cinque, Deniz Gunduz, and Andrea M Tonello

   In International Conference on Machine Learning, 2026

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   This paper presents the first f-divergence-based framework for DM unlearning (f-DMU). We present two classes of loss functions and we theoretically study their convergence properties. We show how H-DMU (derived from the squared Hellinger distance) leads to improved prior preservation.

2025

1. IEEE TNNLS

   

   Copula density neural estimation

   Nunzio A Letizia, Nicola Novello, and Andrea M Tonello

   IEEE Transactions on Neural Networks and Learning Systems, 2025

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   This paper presents an f-divergence-based neural copula estimator, that outperforms other sota neural copula estimators.

2. arXiv

   Robust classification with noisy labels based on posterior maximization

   Nicola Novello and Andrea M Tonello

   arXiv preprint arXiv:2504.06805, 2025
3. SmartGridComm

   

   Data-Driven Grid Monitoring Under Label Noise Using Power Line Modems

   Nicola Novello, Dong Liang, and Andrea M Tonello

   In 2025 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2025
4. ICT Express

   

   Recurrent DQN for radio fingerprinting with constrained measurements collection

   Nicola Novello and Andrea M Tonello

   ICT Express, 2025

2024

1. NeurIPS

   

   Mutual Information Estimation via f -Divergence and Data Derangements

   Nunzio A Letizia, Nicola Novello, and Andrea M Tonello

   Advances in Neural Information Processing Systems, 2024

   Abs PDF Code

   This paper presents an f-divergence-based class of low-variance mutual information neural estimators. Furthermore, it shows how random permutation should be replaced by a data derangement operation, to avoid upper-bounded estimates.

2. ICML

   

   f -Divergence Based Classification: Beyond the Use of Cross-Entropy

   Nicola Novello and Andrea M Tonello

   In International Conference on Machine Learning, 2024

   Abs PDF Code

   This paper presents an f-divergence-based class of objective functions for the estimation of p_X|Y. Then, it shows its applicability for both when X is continuous and when X is discrete (classification).

3. SmartGridComm

   

   Label noise resistant f-divergence receiver for power line communications

   Nicola Novello and Andrea M Tonello

   In 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2024
4. PIMRC

   

   Human Detection Based on Learning and Classification of Radio Scattering Parameters and Para-Hermitian Eigenvalue Decomposition

   Frank E Ebong, Nicola Novello, and Andrea M Tonello

   In 2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2024

2023

1. BalkanCom

   

   Reinforcement learning for simplified training in fingerprinting radio localization

   Nicola Novello and Andrea M Tonello

   In 2023 International Balkan Conference on Communications and Networking (BalkanCom), 2023