关键词: 协同约束, 共生迁移学习, 分类, 支持向量机

Abstract: Transfer learning algorithms usually focus on reusing data of related domains to help solving the learning tasks in the target domain.However,these methods ignore the ability of mutual learning between domains.In this paper,a collaborative constraint based symbiosis transfer learning method (CCSTL) is proposed.Symbiotic transfer mechanism is used to implement mutual learning among domains along with the collaborative constraint.With the help of the iterative optimizations,the proposed method can realize knowledge transfer between the source and target domains.Experimental results on synthetic and real world datasets show the superior or comparable performance of the proposed algorithm compared with existing algorithms.

Key words: collaborative constraints, symbiosis transfer learning, classification, support vector machine