A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such...
Support Vector Machines (SVMs) suffer from an O(n2 ) training cost, where n denotes the number of training instances. In this paper, we propose an algorithm to select boundary ins...
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...