论文标题
随机配置网络的新学习范式：SCN+
A New Learning Paradigm for Stochastic Configuration Network: SCN+
论文作者
论文摘要
使用特权信息（LUPI）范式学习的学习范式启用了教师互动机制，使学习模型在培训阶段使用其他信息。本文是第一个使用lupi范式提出一种名为SCN+的随机配置网络（SCN）的增量学习算法。这种新颖的算法可以在培训阶段将特权信息利用为SCN，该阶段提供了一种新的培训SCN的方法。此外，本文已经研究了融合。最后，实验结果表明SCN+确实表现出色。
Learning using privileged information (LUPI) paradigm, which pioneered teacher-student interaction mechanism, makes the learning models use additional information in training stage. This paper is the first to propose an incremental learning algorithm with LUPI paradigm for stochastic configuration network (SCN), named SCN+. This novel algorithm can leverage privileged information into SCN in the training stage, which provides a new method to train SCN. Moreover, the convergences have been studied in this paper. Finally, experimental results indicate that SCN+ indeed performs favorably.
