: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
— Quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. The method of Stochastic Approxima...
Changing demands, software evolution, and bug fixes require the possibility to update applications as well as system software of embedded devices. Systems that perform updates of ...
In this paper we investigate techniques that allow for on-line updates to columnar databases, leaving intact their high read-only performance. Rather than keeping differential str...