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ORCIDCuong Tran 0007
Person information
- affiliation: Dyania Health, Jersey City, NJ, USA
- affiliation: University of Virginia, Department of Computer Science, VA, USA
- affiliation (PhD): Syracuse University, NY, USA
Other persons with the same name
- Cuong Tran 0001 — Honda Research Institute (and 1 more)
- Cuong Tran 0002 — Alcatel Lucent
- Cuong Tran 0003 — LinkedIn Inc
- Cuong Tran 0004 — UPMC - Sorbonne Universités, CNRS-IMJ, Paris, France
- Cuong Tran 0005 — The University of Manchester, UK
- Cuong Tran 0006 — Singapore University of Technology and Design, Singapore
- Cuong Tran 0008 — University of Information Technology, Ho Chi Minh City, Vietnam (and 1 more)
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2020 – today
- 2024
[c12]Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto:
On The Fairness Impacts of Hardware Selection in Machine Learning. ICML 2024- [c11]Cuong Tran, Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto:
On the Effects of Fairness to Adversarial Vulnerability. IJCAI 2024: 521-529 - [i15]Saswat Das, Marco Romanelli, Cuong Tran, Zarreen Reza, Bhavya Kailkhura, Ferdinando Fioretto:
Low-rank finetuning for LLMs: A fairness perspective. CoRR abs/2405.18572 (2024) - [i14]Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto:
The Data Minimization Principle in Machine Learning. CoRR abs/2405.19471 (2024) - 2023
- [c10]Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck:
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. IJCAI 2023: 501-509 - [c9]Cuong Tran, Ferdinando Fioretto:
On the Fairness Impacts of Private Ensembles Models. IJCAI 2023: 510-518 - [c8]Cuong Tran, Ferdinando Fioretto:
Data Minimization at Inference Time. NeurIPS 2023 - [i13]Cuong Tran, Ferdinando Fioretto:
Personalized Privacy Auditing and Optimization at Test Time. CoRR abs/2302.00077 (2023) - [i12]Cuong Tran, Ferdinando Fioretto:
On the Fairness Impacts of Private Ensembles Models. CoRR abs/2305.11807 (2023) - [i11]Cuong Tran, Ferdinando Fioretto:
Data Minimization at Inference Time. CoRR abs/2305.17593 (2023) - [i10]Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto:
On The Fairness Impacts of Hardware Selection in Machine Learning. CoRR abs/2312.03886 (2023) - 2022
- [c7]Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu:
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey. IJCAI 2022: 5470-5477 - [c6]Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu:
Pruning has a disparate impact on model accuracy. NeurIPS 2022 - [i9]Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu:
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey. CoRR abs/2202.08187 (2022) - [i8]Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck:
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. CoRR abs/2204.05157 (2022) - [i7]Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu:
Pruning has a disparate impact on model accuracy. CoRR abs/2205.13574 (2022) - [i6]Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck:
Fairness Increases Adversarial Vulnerability. CoRR abs/2211.11835 (2022) - 2021
- [c5]Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck:
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. AAAI 2021: 9932-9939 - [c4]Anudit Nagar, Cuong Tran, Ferdinando Fioretto:
Privacy-Preserving and Accountable Multi-agent Learning. AAMAS 2021: 1605-1606 - [c3]Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck, Zhiyan Yao:
Decision Making with Differential Privacy under a Fairness Lens. IJCAI 2021: 560-566 - [c2]Cuong Tran, My H. Dinh, Ferdinando Fioretto:
Differentially Private Empirical Risk Minimization under the Fairness Lens. NeurIPS 2021: 27555-27565 - [i5]Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck:
Decision Making with Differential Privacy under a Fairness Lens. CoRR abs/2105.07513 (2021) - [i4]Anudit Nagar, Cuong Tran, Ferdinando Fioretto:
A Privacy-Preserving and Trustable Multi-agent Learning Framework. CoRR abs/2106.01242 (2021) - [i3]Cuong Tran, My H. Dinh, Ferdinando Fioretto:
Differentially Private Deep Learning under the Fairness Lens. CoRR abs/2106.02674 (2021) - [i2]Cuong Tran, My H. Dinh, Kyle Beiter, Ferdinando Fioretto:
A Fairness Analysis on Private Aggregation of Teacher Ensembles. CoRR abs/2109.08630 (2021) - 2020
- [c1]Ferdinando Fioretto, Pascal Van Hentenryck, Terrence W. K. Mak, Cuong Tran, Federico Baldo, Michele Lombardi:
Lagrangian Duality for Constrained Deep Learning. ECML/PKDD (5) 2020: 118-135 - [i1]Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck:
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. CoRR abs/2009.12562 (2020)
Coauthor Index
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