Parameter-space studies involve running a single application several times with different parameter sets. Since the jobs are mutually independent, many computing resources can be r...
Anand Natrajan, Marty A. Humphrey, Andrew S. Grims...
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We consider the following fundamental scheduling problem. The input consists of n jobs to be scheduled on a set of machines of bounded capacities. Each job is associated with a re...
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...