A novel method for dimensionality reduction of kernel matrix is presented.
提出了基于聚类的核矩阵维度缩减技术。
Uses the adaptive discrete particle swarm algorithm to learn the similar kernel matrix.
通过自适应的离散粒子群算法来对核相似矩阵进行学习。
Decomposition of dynamic matrix becomes a new research topic as soon as the LP dynamic factorization and kernel matrix came out.
随着线性规划动态分解和核心矩阵的出现，矩阵的动态分解成为了一个新的研究课题。
应用推荐