Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Fusing the scores of several biometric systems is a very promising approach to improve the overall system's accuracy. Despite many works in the literature, it is surprising t...
In location-based services, it is common for a user to issue a query based on his/her current position. One such example is "find the available cabs within two miles of my cu...
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...