Phung Lai

According to our database, Phung Lai authored at least 22 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

δ-STEAL: LLM Stealing Attack with Local Differential Privacy.

Kieu Dang, Phung Lai, NhatHai Phan, Yelong Shen, Ruoming Jin, Abdallah Khreishah

CoRR, October, 2025

SoK: Are Watermarks in LLMs Ready for Deployment?

Kieu Dang, Phung Lai, NhatHai Phan, Yelong Shen, Ruoming Jin, Abdallah Khreishah, My T. Thai

CoRR, June, 2025

FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning.

Phung Lai, Xiaopeng Jiang, Hai Phan, Cristian Borcea, Khang Tran, An M. Chen, Vijaya Datta Mayyuri, Ruoming Jin

CoRR, April, 2025

A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning.

Phung Lai, Guanxiong Liu, NhatHai Phan, Issa Khalil, Abdallah Khreishah, Xintao Wu

Proceedings of the 45th IEEE International Conference on Distributed Computing Systems, 2025

2024

FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps.

Xiaopeng Jiang, Han Hu, Thinh On, Phung Lai, Vijaya Datta Mayyuri, An M. Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, NhatHai Phan

IEEE Trans. Mob. Comput., January, 2024

Trustworthiness in Vision-Language Models.

Kiana Vu, Phung Lai

Proceedings of the Computational Data and Social Networks - 13th International Conference, 2024

Navigating Trustworthiness in LLMs: An Examination of Privacy, Security, and Robustness.

Kieu Dang, Phung Lai

Proceedings of the Computational Data and Social Networks - 13th International Conference, 2024

XSub: Explanation-Driven Adversarial Attack against Blackbox Classifiers via Feature Substitution.

Kiana Vu, Phung Lai, Truc Nguyen

Proceedings of the IEEE International Conference on Big Data, 2024

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models.

Thilanka Munasinghe, Phung Lai, Jennifer C. Wei, James A. Hendler, Kimberly A. Cornell

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Differential Privacy in HyperNetworks for Personalized Federated Learning.

Vaisnavi Nemala, Phung Lai, NhatHai Phan

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Active Membership Inference Attack under Local Differential Privacy in Federated Learning.

Truc D. T. Nguyen, Phung Lai, Khang Tran, NhatHai Phan, My T. Thai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

XRand: Differentially Private Defense against Explanation-Guided Attacks.

Truc D. T. Nguyen, Phung Lai, Hai Phan, My T. Thai

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

OnML: an ontology-based approach for interpretable machine learning.

Pelin Ayranci, Phung Lai, NhatHai Phan, Han Hu, Alexander Kolinowski, David Newman, Deijing Dou

J. Comb. Optim., 2022

Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning.

Phung Lai, NhatHai Phan, Abdallah Khreishah, Issa Khalil, Xintao Wu

CoRR, 2022

Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning.

Phung Lai, Han Hu, Hai Phan, Ruoming Jin, My T. Thai, An M. Chen

Proceedings of the Conference on Lifelong Learning Agents, 2022

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks.

Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu

Proceedings of the IEEE International Conference on Big Data, 2022

User-Entity Differential Privacy in Learning Natural Language Models.

Phung Lai, NhatHai Phan, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, Nikolaos Barmpalios

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Continual Learning with Differential Privacy.

Pradnya Desai, Phung Lai, NhatHai Phan, My T. Thai

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

A Novel Attribute-Based Symmetric Multiple Instance Learning for Histopathological Image Analysis.

Trung Vu, Phung Lai, Raviv Raich, Anh T. Pham, Xiaoli Z. Fern, Arvind U. K. Rao

IEEE Trans. Medical Imaging, 2020

Ontology-based Interpretable Machine Learning for Textual Data.

Phung Lai, NhatHai Phan, Han Hu, Anuja Badeti, David Newman, Dejing Dou

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2018

Convmd: Convolutive Matrix Decomposition For Classification Of Matrix Data.

Phung Lai, Raviv Raich, Molly Megraw

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

2016

Jeffreys prior regularization for logistic regression.

Tam Nguyen, Raviv Raich, Phung Lai

Proceedings of the IEEE Statistical Signal Processing Workshop, 2016