弱监督机器学习范式

摘要：

Turn data into information and knowledge,so as to support sound decision making.Key Techniques:Cloud Computing,Managing Data,Crowdsourcing,Collecting Data,Machine Learning,Analyzing Data.Input Space,represented by a single instance (feature vector) characterizing its properties;Output Space,associated with a single label characterizing its semantics.In practice，we usually have to learn with weak supermsion.Semi-Supervised Learning (SSL),Multi-Label Learning(MLL).Learning with Weak Supervision: Framework+Model+Utilization.

关键词： 弱监督机器学习 云计算 数据管理

作者: 张敏灵

会议类型: 国内会议

会议名称: 2017中国人工智能大会

会议地点: 杭州

会议语种:中文

页码: 1-15

在线出版日期: 2017-07-01（万方平台首次上网日期，不代表论文的发表时间）