中国人民大学张琼助理教授：有限混合模型的鲁棒可扩展分布式学习：解决标签切换与拜占庭故障问题
报告摘要
The rise of large-scale and privacy-sensitive data has led to growing demand for distributed statistical learning methods that are both scalable and robust. In this talk, I will present a principled framework for distributed learning of finite mixtur
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