Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
By frame of reference transformations, an input variable in one coordinate system is transformed into an output variable in a different coordinate system depending on another inpu...
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...