智能决策与机器学习研究中心系列讲座(一) 2019-10-30


题目: Learning theory for distributed learning

报告人:林绍波,tyc234cc 太阳成集团教授

时间:2019年11月4日(周一)下午15:00-16:30

地点:管院313会议室

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报告内容: We analyze the performance of distributed learning based on a divide-and-conquer strategy.  This scheme applies a specified learning algorithm to data subsets that are distributively stored on multiple servers to produce individual output functions, and then takes a weighted average of the individual output functions as a final estimator.  We study that under which condition distributed learning is feasible and conduct several strategies such as semi-supervised distributed learning and communications to improve its performance further.

 

报告人简介:林绍波,tyc234cc 太阳成集团教授,青年拔尖人才。博士毕业于tyc234cc 太阳成集团数学与统计学院。曾先后于香港城市大学数学系、香港理工大学应用数学系、香港城市大学数据科学学院担任博士后、副研究员、研究员。研究方向为大数据分析、分布式计算及深度学习。主持或以核心成员参与国家自然科学基金9项。 在Journal of Machine Learning Research, Applied and Computational Harmonics Analysis, IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks and Learning Systems等著名期刊发表论文50余篇。