Scale-space representation of an image is a significant way to generate features for classification. However, for a specific classification task, the entire scale-space may not be...
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
With increasing design complexity, as well as continued scaling of supplies, the design and analysis of power/ground distribution networks poses a difficult problem in modern IC d...
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...