【专家简介】：毛晓军，研究领域包括分布式统计推断，推荐系统和高维数据分析。主要研究成果发表于JASA, JMLR, IEEE TIT, IEEE TSP, ICML,《管理世界》等。先后主持国自然面上项目和青年基金等。
【报告摘要】：Distributed learning has been extensively studied and applied in various machine-learning scenarios. This talk initiates by revisiting several classical optimization algorithms, namely gradient descent, stochastic gradient descent (SGD), proximal gradient descent, and ADMM. Following this, we broaden the application of these algorithms to centralized and decentralized distributed frameworks. In particular, we introduce distributed learning algorithms including Communication-efficient Surrogate Likelihood (CSL) and some basic decentralized consensus algorithms.
时间：2023年12月28日 8:45 – 10:45
腾讯会议：532-676-328
