报告主题：A New Framework for the Study of Multi label Classification

时间：2024年3月15日13:00-13:45

地点：上川路校区二教105/腾讯会议 会议号：517 4242 8784密码：6666

报告人：刘文臣

报告内容简介：

Nowadays, multi-label classification methods are increasingly required by modern applications, such as gene function classification, music categorization and birds classification. In this paper, a new framework for multi label classification is built. Starting from marginal loss functions not necessarily derived from probability distributions, we utilize an additive over-parametrization with shrinkage to incorporate label dependencies into the criterion. The non-convex robust loss functions is used to reduce the influence of mislabeling labels. A joint regularization method by sparsity and rank reduction method to deal with high dimension data. Masking method is used to handle missing labels. Simulation and real data analysis shows the power of this new method. The new method not only builds a multi-label classification model for yeast genes data, but also captures the dependencies of the yeast genes data between the phylogenetic mapping.

主讲人简介：

刘文臣，上海立信会计金融学院副教授，常任轨教师，主要研究方向有多元响应变量的相依性及其回归问题的研究，统计优化，贝叶斯统计，零一膨胀模型。