Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
We attack the task of predicting which news-stories are more appealing to a given audience by comparing ‘most popular stories’, gathered from various online news outlets, over ...
Elena Hensinger, Ilias N. Flaounas, Nello Cristian...
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
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...