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20222026
most citedConstraint-Free Structure Learning with Smooth Acyclic Orientations

1 citations · 1 across the 6 of their papers we have counts for

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cs.LG2026

Z-PEFT: Zero-shot Backdoor Detection in Parameter-Efficient Fine-Tuning via Canonical Spectral Signatures

Nicola Pitzalis, Donald Shenaj, Giacomo Cignoni +3

Parameter-Efficient Fine-tuned (PEFT) models are frequently downloaded from open repositories by practitioners. This widespread practice creates a significant attack surface, as ma…

cs.LG2026

A Practical Guide to Streaming Continual Learning

Andrea Cossu, Federico Giannini, Giacomo Ziffer +5

Continual Learning (CL) and Streaming Machine Learning (SML) study the ability of agents to learn from a stream of non-stationary data. Despite sharing some similarities, they addr…

cs.LG2023

Neural Autoencoder-Based Structure-Preserving Model Order Reduction and Control Design for High-Dimensional Physical Systems

Marco Lepri, Davide Bacciu, Cosimo Della Santina

This work concerns control-oriented and structure-preserving learning of low-dimensional approximations of high-dimensional physical systems, with a focus on mechanical systems. We…

cs.LG2023

Classifier-free graph diffusion for molecular property targeting

Matteo Ninniri, Marco Podda, Davide Bacciu

This work focuses on the task of property targeting: that is, generating molecules conditioned on target chemical properties to expedite candidate screening for novel drug and mate…

cs.LG2023★ 1 cited

Constraint-Free Structure Learning with Smooth Acyclic Orientations

Riccardo Massidda, Francesco Landolfi, Martina Cinquini +1

The structure learning problem consists of fitting data generated by a Directed Acyclic Graph (DAG) to correctly reconstruct its arcs. In this context, differentiable approaches co…