This is the first book that treats the fields ofsupervised, semi-supervised and unsupervised machine learningin a unifying way. In particular,it is the first presentation of the standard and improved graph based semisupervised (manifold) algorithms in a textbook. The book presents both the theory ...
Kernel-based algorithms and visualization for interval data mining. Thanh-Nghi Do,Poulet F. 2006 Sixth IEEE International Conference on Data Mining Workshops . 2006Thanh-Nghi Do,Poulet F. Kernel-based algorithms and visualization for interval data mining[A].Hongkong:IEEE Press,2006.295-299....
We present several generative and predictive algorithms based on the RKHS (reproducing kernel Hilbert spaces) methodology, which most importantly are scalable in the following sense. It is well recognized that the RKHS methodology leads one to efficient and robust algorithms for numerous tasks in data...
Density-based spatial clustering algorithms, which have been well studied in database domains, are based on densities of geospatial data. Recently, the siz... T Sakai,K Tamura,K Misaki,... 被引量: 1发表: 2016年 加载更多研究点推荐 spatial data unsupervised learning kernel methods 站内活动 ...
"Fast bounded online gradient descent algorithms for scalable kernel-based online learning." arXiv preprint arXiv:1206.4633 (2012).P. Zhao, J. Wang, P. Wu, R. Jin, and S. C. Hoi. Fast bounded online gradient descent algorithms for scalable kernel-based online learning. arXiv preprint ar...
learning models and algorithms. This also makes it easier to achieve out-of-sample generalization. Moreover, we focus on learning metrics because this allows us to formulate the met- ric learning problembased on the kernel approach [Sch¨ olkopf ...
Also, two of the most widely used perfor- mance indexes have been modified using kernel distance function for the eval- uation of kernel based algorithms. Comparison between RFCM and proposed K-RFCM has been done on a wide variety of datasets to obtain favourable re- sults. From the ...
The Genetic Algorithms (GAs), Artificial Neural Network (ANN) and numerical simulation are applied to study the problem. A synthetic procedure based on ... 陳宇文,YuWen Chen,張良正,... 被引量: 1发表: 1999年 利用類完全互補碼於蜂巢式正交分頻多工系統中基地台搜尋之進一步研究 (OFDM) system...
Many multi-instance learning algorithms have been intensively studied during this decade, such as the Diverse Density (DD) algorithm [6], multi-label multi-instance learning (MLMIL) [7], and neural network algorithm [8]. It is difficult to list all existing MIL algorithms. Here, we mainly ...
In Section 4, we use Theorem 3.2 to prove convergence for two popular classes of greedy algorithms: the \beta -greedy algorithm (Theorem 4.1) and the geometric greedy algorithm of [4] (Theorem 4.2). Supporting numerical results on kernel-based interpolation from scattered Radon data are ...