1
Cross-Cluster Weighted Forests
跨簇加权森林巧妙利用数据异质性，为生物应用构建更可信的集成学习模型
arXiv:2105.07610v5 Announce Type: replace-cross Abstract: Building trustworthy machine learning algorithms for biological applications requires adapti…
2
FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning
用模型归因对抗联邦学习数据异质性，思路新颖且直击分布式训练痛点
arXiv:2606.31742v1 Announce Type: cross Abstract: Explainable AI (XAI) methods have demonstrated significant success in recent years at identifying re…