Zhimin Mei — accepted AI-conference papers

2026

Fair Dataset Distillation via Cross-Group Barycenter Alignment

Mohammad Hossein Moslemi, Nima Hosseini Dashtbayaz, Zhimin Mei, Boyu Wang, Bissan Ghaddar

ICML 2026poster

Dataset Distillation aims to compress a large dataset into a small synthetic one while maintaining predictive performance. We show that as different demographic groups exhibit distinct predictive patterns, the distillation process struggles to simultaneously preserve informative signals for all subg…

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2026

Graph Domain Adaptation via Homophily-Agnostic Reconstructing Structure

Ruiyi Fang, Shuo Wang, Ruizhi Pu, QIUHAO Zeng, Hao Zheng, Ziyan Wang +5

AAAI 2026technical

Graph Domain Adaptation (GDA) transfers knowledge from labeled source graphs to unlabeled target graphs, addressing the challenge of label scarcity. However, existing GDA methods typically assume that both source and target graphs exhibit homophily, leading existing methods to perform poorly when he

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