Kernel methods have been successfully applied in various applications. To succeed in these
applications, it is crucial to learn a good kernel representation, whose objective is to reveal …

Fuzzy rough sets, generalized from Pawlak's rough sets, were introduced for dealing with
continuous or fuzzy data. This model has been widely discussed and applied these years. It …

The objective of sparse metric learning is to learn a distance measure from a set of data in
addition to finding a low-dimensional representation. Despite demonstrated success, the …

This paper proposes a new classifier called density-induced margin support vector
machines (DMSVMs). DMSVMs belong to a family of SVM-like classifiers. Thus, DMSVMs …

提出了一种能够保护数据隐私的协作式分类机制, 即C2MP2 (collaborative classification
mechanismfor privacy-preserving), 该算法利用2 类样本各自的均值和协方差作为整体信息 …

Standard support vector machines (SVMs) have kernels based on the Euclidean distance.
This brief extends standard SVMs to SVMs with kernels based on the Mahalanobis distance …

摘要文章旨在研究数据分布未知的高维, 小样本问题的特征抽取算法. 基于支持向量机原理和
特征统计不相关思想, 提出基于散度支持向量机(SSVM) 的递归统计不相关特征抽取算法 …

Machine learning is a research area that focuses on designing and developing algorithms
for computers to evolve behaviors based on empirical data [114]. A center problem in …

为实现石油场站中长输管道状态的智能化监控, 提出一个融合无线传感器网络(WSN), GPRS
和Internet 的监控系统. 基于WIA-PA 无线工业标准, 进行WSN 的硬件集成 …

摘要提出了一种协作式整体局部分类算法, 即C2M (Collaborative classification machine with
local and global information), 该算法利用两类样本各自的协方差作为整体方向信息 …