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stat.ML2026
Membership Inference via Pairwise Likelihood Ratios
Shengjie Niu, Zebin Yun, Yeheng Ge +1
Membership inference attacks (MIAs) are the standard tool for auditing the privacy risks of machine learning models. Given a query point, an MIA aims to determine whether that poin…
stat.ML2025
Learning Guarantee of Reward Modeling Using Deep Neural Networks
Yuanhang Luo, Yeheng Ge, Ruijian Han +1
In this work, we study the learning theory of reward modeling with pairwise comparison data using deep neural networks. We establish a novel non-asymptotic regret bound for deep re…
stat.ML2025
Transfer Learning through Enhanced Sufficient Representation: Enriching Source Domain Knowledge with Target Data
Yeheng Ge, Xueyu Zhou, Jian Huang
Transfer learning is an important approach for addressing the challenges posed by limited data availability in various applications. It accomplishes this by transferring knowledge…