中国电子科技2004，Vol.2Issue(4)：29-36,8.
Incremental POP Learning
Incremental POP Learning
摘要
Abstract
In recently proposed partial oblique projection (POP) learning, a function space is decomposed into two complementary subspaces, so that functions belonging to one of which can be optimally estimated. This paper shows that when the decomposition is specially performed so that the above subspace becomes the largest, a special learning called SPOP learning is obtained and correspondingly an incremental learning is implemented, result of which equals exactly to that of batch learning including novel data. The effectiveness of the method is illustrated by experimental results.关键词
supervised learning/generalization ability/POP learning/incremental learningKey words
supervised learning/generalization ability/POP learning/incremental learning分类
信息技术与安全科学引用本文复制引用
LIU Ben-yong..Incremental POP Learning[J].中国电子科技,2004,2(4):29-36,8.基金项目
The related work is benefited from discussions with Prof. H. Ogawa of Tokyo Institute of Technology on A Family of Projection Learning for Incremental and Active Learning, and partly supported by the Young Scholar Foundation of UESTC (No.JX200402). （No.JX200402）
