Dingfan Chen

According to our database, Dingfan Chen authored at least 16 papers between 2019 and 2024.

Collaborative distances:

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

2024

A Unified View of Differentially Private Deep Generative Modeling.

Dingfan Chen, Raouf Kerkouche, Mario Fritz

Trans. Mach. Learn. Res., 2024

FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations.

Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz

Proc. Priv. Enhancing Technol., 2024

Towards Biologically Plausible and Private Gene Expression Data Generation.

Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz

CoRR, 2024

PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics.

Derui Zhu, Dingfan Chen, Qing Li, Zongxiong Chen, Lei Ma, Jens Grossklags, Mario Fritz

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Inside the Black Box: Detecting Data Leakage in Pre-Trained Language Encoders.

Yuan Xin, Zheng Li, Ning Yu, Dingfan Chen, Mario Fritz, Michael Backes, Yang Zhang

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Towards privacy-preserving machine learning: generative modeling and discriminative analysis.

Dingfan Chen

PhD thesis, 2023

Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy.

Derui Zhu, Dingfan Chen, Jens Grossklags, Mario Fritz

CoRR, 2023

Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy.

Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz

CoRR, 2023

MargCTGAN: A "Marginally" Better CTGAN for the Low Sample Regime.

Tejumade Afonja, Dingfan Chen, Mario Fritz

Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022

Private Set Generation with Discriminative Information.

Dingfan Chen, Raouf Kerkouche, Mario Fritz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Responsible Disclosure of Generative Models Using Scalable Fingerprinting.

Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry S. Davis, Mario Fritz

Proceedings of the Tenth International Conference on Learning Representations, 2022

RelaxLoss: Defending Membership Inference Attacks without Losing Utility.

Dingfan Chen, Ning Yu, Mario Fritz

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements.

Xiaoyi Chen, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, Yang Zhang

Proceedings of the ACSAC '21: Annual Computer Security Applications Conference, Virtual Event, USA, December 6, 2021

2020

GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators.

Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models.

Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz

Proceedings of the CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020

2019

GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs.

Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz

CoRR, 2019