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2020年1月7日学术报告(刘凯 助理教授 美国克莱姆森大学)
2020年01月03日16时 人评论

报告题目:矩阵分析在机器学习中的应用

报告时间:202017日(周二)下午14:30

报告地点:网赌最佳平台B404会议室

报告人:刘凯 

报告人单位:美国克莱姆森大学

报告人简介: 

Dr. Kai Liu received his Ph.D. degree from Colorado School of Mines, USA in 2019 and now he is a tenure-track Assistant Professor in Computer Science Division, Clemson University, South Carolina. His research interest lies in Machine Learning with its applications in Artificial Intelligence, Computer Vision, Natural Language Processing, Speech Recognition, Data Mining and Bioinformatics with provable theoretical guarantees. He has published 10+ papers in prestigious conferences such as CVPR/AAAI/ACL/NeurIPS/IJCAI/ SDM/RECOMB etc.

报告摘要 

Optimization is one of the most important research areas in machine learning. Many problems such as clustering, dictionary learning, principal component analysis, data recovery and compressed sensing can be transformed into optimization formulation, where Matrix factorization and analysis play an important role. PALM (Proximal Alternating Linearized Minimization) was proposed recently and has been proved to be an efficient algorithm in solving multivariable optimization with nice mathematical guarantee. In this talk, I am going to show the connection of PALM and classical gradient descent method followed by discussing its variations, applications and several open problems.

邀请人:王峰 副教授、蒋华 讲师


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