: 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 ...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Sense tagged corpus plays a very crucial role to Natural Language Processing, especially on the research of word sense disambiguation and natural language understanding. Having a l...
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...