Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations. - Steffen Schotthöfer; Emanuele Zangrando; Jonas Kusch; Gianluca Ceruti; Francesco Tudisco (NeurIPS, 2022)

Robust low-rank training via approximate orthonormal constraints. - Dayana Savostianova; Emanuele Zangrando; Gianluca Ceruti; Francesco Tudisco (NeurIPS, 2023)

HIJACK: Learning-based Strategies for Sound Classification Robustness to Adversarial Noise. - Derek Sweet; Emanuele Zangrando; Francesca Meneghello 001 (SMARTCOMP, 2023)

Rank-adaptive spectral pruning of convolutional layers during training. - Emanuele Zangrando; Steffen Schotthöfer; Gianluca Ceruti; Jonas Kusch; Francesco Tudisco (CoRR, 2023)

Geometry-aware training of factorized layers in tensor Tucker format. - Emanuele Zangrando; Steffen Schotthöfer; Gianluca Ceruti; Jonas Kusch; Francesco Tudisco (NeurIPS, 2024)

Neural Rank Collapse: Weight Decay and Small Within-Class Variability Yield Low-Rank Bias. - Emanuele Zangrando; Piero Deidda; Simone Brugiapaglia; Nicola Guglielmi; Francesco Tudisco (CoRR, 2024)

Low-Rank Adversarial PGD Attack. - Dayana Savostianova; Emanuele Zangrando; Francesco Tudisco (CoRR, 2024)

GeoLoRA: Geometric integration for parameter efficient fine-tuning. - Steffen Schotthöfer; Emanuele Zangrando; Gianluca Ceruti; Francesco Tudisco; Jonas Kusch (ICLR, 2025)

dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation. - Emanuele Zangrando; Sara Venturini; Francesco Rinaldi; Francesco Tudisco (ICLR, 2025)