An incremental learning algorithm using multiple support vector machines (SVMs) is proposed.
给出了使用多支持向量机进行增量学习的算法。
An incremental learning method for EHW based on knowledge acquirement was proposed and EHW-oriented learning mechanism was constructed.
本文构造了一种基于知识的递增式学习模式，研究了一种面向EHW的自适应学习机制。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
We want our children to accept learning as a natural consequence of living, and an ongoing incremental process that continues throughout life.
我们希望我们的孩子把学习当作是生活的一种自然结果，循序渐进，贯穿一生。
Presents an improved incremental learning algorithm based on KKT conditions.
提出了一种改进的基于KKT条件的增量学习算法。
The main contributions of this paper are listed as follows. (1) An incremental tensor subspace learning based object tracking is presented.
主要研究内容包括：(1)提出一种增量式张量子空间学习的目标跟踪算法。
This paper presents an adaptive and iterative support vector machine regression algorithm (CAISVR) based on chunking incremental learning and decremental learning procedures.
文中基于块增量学习和逆学习过程，提出了自适应迭代回归算法。
The experiments show that IBN-M algorithm can learn comparatively accurate network from the extremely large dataset. IBN-M is an interesting improvement for incremental learning Bayesian Network.
实验结果表明IBN-M算法在数据缺失下贝叶斯网络的增量学习中确实能够学出相对精确的网络模型，该算法也是对贝叶斯网络增量学习方面的一个必要的补充。
The experiments show that IBN-M algorithm can learn comparatively accurate network from the extremely large dataset. IBN-M is an interesting improvement for incremental learning Bayesian Network.
实验结果表明IBN-M算法在数据缺失下贝叶斯网络的增量学习中确实能够学出相对精确的网络模型，该算法也是对贝叶斯网络增量学习方面的一个必要的补充。
应用推荐