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cs.CR2024
Watermarking Generative Categorical Data
Bochao Gu, Hengzhi He, Guang Cheng
In this paper, we propose a novel statistical framework for watermarking generative categorical data. Our method systematically embeds pre-agreed secret signals by splitting the da…
cs.CR2024★ 1 cited
Watermarking Continuous Tabular Data Generation
Hengzhi He, Peiyu Yu, Junpeng Ren +2
In this paper, we introduce a simple yet effective tabular data watermarking mechanism with statistical guarantees. We show theoretically that the proposed watermark can be effecti…
cs.LG2024
"Noisier" Noise Contrastive Eestimation is (Almost) Maximum Likelihood
Peiyu Yu, Dinghuai Zhang, Hengzhi He +10
Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing challenge remains: accurately estimating r…