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cs.LG2025
A Unified Framework for Diffusion Model Unlearning with f-Divergence
Nicola Novello, Federico Fontana, Luigi Cinque +2
Most existing methods for concept unlearning in text-to-image diffusion models minimize a mean squared error (MSE) loss between the denoiser outputs conditioned on a target and an…
cs.LG2025
Robust Classification with Noisy Labels Based on Posterior Maximization
Nicola Novello, Andrea M. Tonello
Designing objective functions robust to label noise is crucial for real-world classification algorithms. In this paper, we investigate the robustness to label noise of an -diver…