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Dingfan Chen
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2020 – today
- 2024
- [j2]Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz:
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations. Proc. Priv. Enhancing Technol. 2024(3): 372-390 (2024) - [j1]Dingfan Chen, Raouf Kerkouche, Mario Fritz:
A Unified View of Differentially Private Deep Generative Modeling. Trans. Mach. Learn. Res. 2024 (2024) - [i11]Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz:
Towards Biologically Plausible and Private Gene Expression Data Generation. CoRR abs/2402.04912 (2024) - [i10]Derui Zhu, Dingfan Chen, Qing Li, Zongxiong Chen, Lei Ma, Jens Grossklags, Mario Fritz:
PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics. CoRR abs/2404.04722 (2024) - 2023
- [b1]Dingfan Chen:
Towards privacy-preserving machine learning: generative modeling and discriminative analysis. Saarland University, Saarbrücken, Germany, 2023 - [c7]Tejumade Afonja
, Dingfan Chen
, Mario Fritz
:
MargCTGAN: A "Marginally" Better CTGAN for the Low Sample Regime. DAGM 2023: 524-537 - [i9]Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz:
Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy. CoRR abs/2302.01068 (2023) - [i8]Derui Zhu, Dingfan Chen, Jens Grossklags, Mario Fritz:
Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy. CoRR abs/2302.07801 (2023) - [i7]Tejumade Afonja, Dingfan Chen, Mario Fritz:
MargCTGAN: A "Marginally" Better CTGAN for the Low Sample Regime. CoRR abs/2307.07997 (2023) - [i6]Dingfan Chen, Raouf Kerkouche, Mario Fritz:
A Unified View of Differentially Private Deep Generative Modeling. CoRR abs/2309.15696 (2023) - 2022
- [c6]Dingfan Chen, Ning Yu, Mario Fritz:
RelaxLoss: Defending Membership Inference Attacks without Losing Utility. ICLR 2022 - [c5]Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry S. Davis, Mario Fritz:
Responsible Disclosure of Generative Models Using Scalable Fingerprinting. ICLR 2022 - [c4]Dingfan Chen, Raouf Kerkouche, Mario Fritz:
Private Set Generation with Discriminative Information. NeurIPS 2022 - [i5]Dingfan Chen, Ning Yu, Mario Fritz:
RelaxLoss: Defending Membership Inference Attacks without Losing Utility. CoRR abs/2207.05801 (2022) - [i4]Dingfan Chen, Raouf Kerkouche, Mario Fritz:
Private Set Generation with Discriminative Information. CoRR abs/2211.04446 (2022) - 2021
- [c3]Xiaoyi Chen
, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, Yang Zhang:
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements. ACSAC 2021: 554-569 - 2020
- [c2]Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz:
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models. CCS 2020: 343-362 - [c1]Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz:
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators. NeurIPS 2020 - [i3]Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz:
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators. CoRR abs/2006.08265 (2020) - [i2]Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry Davis, Mario Fritz:
Responsible Disclosure of Generative Models Using Scalable Fingerprinting. CoRR abs/2012.08726 (2020)
2010 – 2019
- 2019
- [i1]Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz:
GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs. CoRR abs/1909.03935 (2019)
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last updated on 2024-08-10 01:22 CEST by the dblp team
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