Lagrangian Duality for Constrained Deep Learning. - Ferdinando Fioretto; Pascal Van Hentenryck; Terrence W. K. Mak; Cuong Tran 007; Federico Baldo; Michele Lombardi 001 (ECML/PKDD (5), 2020)

Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. - Cuong Tran 007; Ferdinando Fioretto; Pascal Van Hentenryck (AAAI, 2021)

Privacy-Preserving and Accountable Multi-agent Learning. - Anudit Nagar; Cuong Tran 007; Ferdinando Fioretto (AAMAS, 2021)

Decision Making with Differential Privacy under a Fairness Lens. - Cuong Tran 007; Ferdinando Fioretto; Pascal Van Hentenryck; Zhiyan Yao (IJCAI, 2021)

Differentially Private Empirical Risk Minimization under the Fairness Lens. - Cuong Tran 007; My H. Dinh; Ferdinando Fioretto (NeurIPS, 2021)

Decision Making with Differential Privacy under a Fairness Lens. - Ferdinando Fioretto; Cuong Tran 007; Pascal Van Hentenryck (CoRR, 2021)

A Privacy-Preserving and Trustable Multi-agent Learning Framework. - Anudit Nagar; Cuong Tran 007; Ferdinando Fioretto (CoRR, 2021)

Differentially Private Deep Learning under the Fairness Lens. - Cuong Tran 007; My H. Dinh; Ferdinando Fioretto (CoRR, 2021)

A Fairness Analysis on Private Aggregation of Teacher Ensembles. - Cuong Tran 007; My H. Dinh; Kyle Beiter; Ferdinando Fioretto (CoRR, 2021)

Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey. - Ferdinando Fioretto; Cuong Tran 007; Pascal Van Hentenryck; Keyu Zhu (IJCAI, 2022)

Pruning has a disparate impact on model accuracy. - Cuong Tran 007; Ferdinando Fioretto; Jung-Eun Kim; Rakshit Naidu (NeurIPS, 2022)

Fairness Increases Adversarial Vulnerability. - Cuong Tran 007; Keyu Zhu; Ferdinando Fioretto; Pascal Van Hentenryck (CoRR, 2022)

On the Fairness Impacts of Private Ensembles Models. - Cuong Tran 007; Ferdinando Fioretto (IJCAI, 2023)

SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. - Cuong Tran 007; Keyu Zhu; Ferdinando Fioretto; Pascal Van Hentenryck (IJCAI, 2023)

Data Minimization at Inference Time. - Cuong Tran 007; Ferdinando Fioretto (NeurIPS, 2023)

Personalized Privacy Auditing and Optimization at Test Time. - Cuong Tran 007; Ferdinando Fioretto (CoRR, 2023)

On The Fairness Impacts of Hardware Selection in Machine Learning. - Sree Harsha Nelaturu; Nishaanth Kanna Ravichandran; Cuong Tran 007; Sara Hooker; Ferdinando Fioretto (ICML, 2024)

On the Effects of Fairness to Adversarial Vulnerability. - Cuong Tran 007; Keyu Zhu; Pascal Van Hentenryck; Ferdinando Fioretto (IJCAI, 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)

The Data Minimization Principle in Machine Learning. - Prakhar Ganesh; Cuong Tran 007; Reza Shokri; Ferdinando Fioretto (FAccT, 2025)