Feature Selection with Rényi Min-Entropy. - Catuscia Palamidessi; Marco Romanelli 002 (ANNPR, 2018)

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data. - Mattia Dalsass; Margherita Bodini; Christophe G. Lambert; Marie-Cécile Mortier; Marco Romanelli 002; Duccio Medini; Alessandro Muzzi; Alessandro Brozzi (BMC Bioinform., 2019)

Generating Optimal Privacy-Protection Mechanisms via Machine Learning. - Marco Romanelli 002; Catuscia Palamidessi; Konstantinos Chatzikokolakis 001 (CoRR, 2019)

Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy. - Moreno Falaschi; Catuscia Palamidessi; Marco Romanelli 002 (Gabbrielli's Festschrift, 2020)

Estimating g-Leakage via Machine Learning. - Marco Romanelli 002; Konstantinos Chatzikokolakis 001; Catuscia Palamidessi; Pablo Piantanida (CCS, 2020)

Modern Applications of Game-Theoretic Principles (Invited Paper). - Catuscia Palamidessi; Marco Romanelli 002 (CONCUR, 2020)

Optimal Obfuscation Mechanisms via Machine Learning. - Marco Romanelli 002; Konstantinos Chatzikokolakis 001; Catuscia Palamidessi (CSF, 2020)

Feature selection in machine learning: Rényi min-entropy vs Shannon entropy. - Catuscia Palamidessi; Marco Romanelli 002 (CoRR, 2020)

Machine learning methods for privacy protection : leakage measurement and mechanisms design. (Méthodes d'apprentissage machine pour la protection de la vie privée : mesure de leakage et design des mécanismes). - Marco Romanelli 002 (2020)

DOCTOR: A Simple Method for Detecting Misclassification Errors. - Federica Granese; Marco Romanelli 002; Daniele Gorla; Catuscia Palamidessi; Pablo Piantanida (NeurIPS, 2021)

MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors. - Federica Granese; Marine Picot; Marco Romanelli 002; Francesco Messina; Pablo Piantanida (ECML/PKDD (3), 2022)

MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors. - Federica Granese; Marine Picot; Marco Romanelli 002; Francisco Messina; Pablo Piantanida (CoRR, 2022)

A Minimax Approach Against Multi-Armed Adversarial Attacks Detection. - Federica Granese; Marco Romanelli 002; Siddharth Garg; Pablo Piantanida (CoRR, 2023)

INVICTUS: Optimizing Boolean Logic Circuit Synthesis via Synergistic Learning and Search. - Animesh Basak Chowdhury; Marco Romanelli 002; Benjamin Tan 001; Ramesh Karri; Siddharth Garg (CoRR, 2023)

A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection. - Marine Picot; Federica Granese; Guillaume Staerman; Marco Romanelli 002; Francisco Messina; Pablo Piantanida; Pierre Colombo (Trans. Mach. Learn. Res., 2023)

Optimal Zero-Shot Detector for Multi-Armed Attacks. - Federica Granese; Marco Romanelli 002; Pablo Piantanida (AISTATS, 2024)

On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem. - Georg Pichler; Marco Romanelli 002; Divya Prakash Manivannan; Prashanth Krishnamurthy; Farshad Khorrami; Siddharth Garg (AISTATS, 2024)

Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization. - Animesh Basak Chowdhury; Marco Romanelli 002; Benjamin Tan 001; Ramesh Karri; Siddharth Garg (ICLR, 2024)

A Data-Driven Measure of Relative Uncertainty for Misclassification Detection. - Eduardo Dadalto Câmara Gomes; Marco Romanelli 002; Georg Pichler; Pablo Piantanida (ICLR, 2024)

Beyond the Norms: Detecting Prediction Errors in Regression Models. - Andrés Altieri; Marco Romanelli 002; Georg Pichler; Florence Alberge; Pablo Piantanida (ICML, 2024)

Disparate Impact on Group Accuracy of Linearization for Private Inference. - Saswat Das; Marco Romanelli 002; Ferdinando Fioretto (ICML, 2024)

Low-rank finetuning for LLMs: A fairness perspective. - Saswat Das; Marco Romanelli 002; Cuong Tran 007; Zarreen Reza; Bhavya Kailkhura; Ferdinando Fioretto (CoRR, 2024)

Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning. - Georg Pichler; Marco Romanelli 002; Leonardo Rey Vega; Pablo Piantanida (IEEE Trans. Dependable Secur. Comput., 2024)

Optimal Zero-shot Regret Minimization for Selective Classification with Out-of-Distribution Detection. - Eduardo Dadalto Câmara Gomes; Marco Romanelli 002 (UAI, 2025)