Publications
Patents
Training Language Models and Preserving Privacy. Phung Lai, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, Nikolaos Barmpalios, Target filling date for Non-provisional US Patent: 21/02/2023.
Privacy-Aware Language Models Training. Phung Lai, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, Nikolaos Barmpalios, Provisional Adobe Patent 2022.
Preserving User-Entity Differential Privacy in Natural Language Modeling. Phung Lai, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, Nikolaos Barmpalios, Non-provisional US Patent 2021 (To be published in Feb 2023).
User-Entity Differential Privacy in Natural Language Modeling. Phung Lai, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, Nikolaos Barmpalios, Provisional Adobe Patent 2021.
Publications
2023
How to Backdoor HyperNetwork in Personalized Federated Learning? Phung Lai, Hai Phan, Issa Khalil, Abdallah Khreishah, Xintao Wu. NeurIPS-BUGS 2023.
Differential Privacy in HyperNetworks for Personalized Federated Learning. Vaisnavi Nemala, Phung Lai, and Hai Phan. CIKM 2023. Short Paper (acceptance rate: 152/554).
Active Membership Inference Attack under Local Differential Privacy in Federated Learning. Truc Nguyen, Phung Lai, Khang Tran, NhatHai Phan, and My T. Thai. AISTATS 2023.
XRand: Differentially Private Defense against Explanation-Guided Attacks. Truc Nguyen*, Phung Lai*, NhatHai Phan, and My T. Thai. AAAI 2023. (acceptance rate 19%: 1,721 / 8,777) (*: Co-first author) [Distinguished Paper Award (12 selected/8,777)]
2022
User-Entity Differential Privacy in Learning Natural Language Models. Phung Lai, NhatHai Phan, Tong Sun, Rajiv Jain, Franck Dernoncourt, Jiuxiang Gu, and Nikolaos Barmpalios. IEEE BigData 2022. Regular Paper (acceptance rate: 122/633). [Github] [Oral Presentation]
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning. Phung Lai, Han Hu, NhatHai Phan, Ruoming Jin, My Thai, An Chen. The Conference on Lifelong Learning Agents (CoLLAs 2022), Proceedings of Machine Learning Research (PMLR). (* corresponding author)
OnML: An Ontology-based Approach for Interpretable Machine Learning. Pelin Ayranci*, Phung Lai*, NhatHai Phan, Han Hu, David Newman, Alexander Kalinowski, and Dejing Dou. Journal of Combinatorial Optimization - Springer. (*: Co-first author)
FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps. Xiaopeng Jiang*, Han Hu*, Thinh On, Phung Lai, Vijaya Datta Mayyuri, An Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, and NhatHai Phan. IEEE Transactions on Mobile Computing (IEEE TMC). (*: Co-first author)
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Thai, and Xintao Wu. IEEE BigData 2022. [Oral Presentation]
2021
Continual Learning with Differential Privacy. Pradnya Desai*, Phung Lai*, NhatHai Phan, and My T. Thai. The 28th International Conference on Neural Information Processing (ICONIP'21), December 8 - 12, 2021. [Oral Presentation] [Github] (*: Co-first author) (Pradnya Desai is an honor undergraduate student, under my supervision)
2020
A novel Attribute-based Symmetric Multiple Instance Learning for Histopathological Image Analysis. Trung Vu*, Phung Lai*, Raviv Raich, Anh Pham, Xiaoli Z Fern, UK Arvind Rao. IEEE Transactions on Medical Imaging (IEEE T-MI), October 2020. (*: Co-first author)
Ontology-based Interpretable Machine Learning for Textual Data. Phung Lai, NhatHai Phan, Han Hu, Anuja Badeti, David Newman, and Dejing Dou. The International Joint Conference on Neural Networks (IJCNN'20), July 19 - 24th, 2020, Glasgow (UK). [Github] [Oral Presentation]
2019
Ontology-based Interpretable Machine Learning with Learnable Anchors. Phung Lai, NhatHai Phan, David Newman, Han Hu, Anuja Badeti, and Dejing Dou. Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) Workshop at NeurIPS'19, December 8-14, 2019, Vancouver, Canada. [Oral Presentation] [pdf]
2018
ConvMD: Convolutive matrix decomposition for classification of matrix data. Phung Lai, Raviv Raich, and Molly Megraw. IEEE Statistical Signal Processing (SSP) Workshop, June 10-13, 2018, Freiburg im Breisgau, Germany. [Oral Presentation] [pdf]
2016
Jeffreys prior regularization for logistic regression. Tam Nguyen, Raviv Raich, Phung Lai. IEEE Statistical Signal Processing (SSP) Workshop, June 10-13, 2018, Freiburg im Breisgau, Germany. [Oral Presentation] [pdf]