Abstract-- Reinforcement Programming (RP) is a new approach to automatically generating algorithms, that uses reinforcement learning techniques. This paper describes the RP approac...
Spencer K. White, Tony R. Martinez, George L. Rudo...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
—Due to the difficulty and thus effort and expenses involved in creating them, personalization strategies in learning environments have to demonstrate a higher returnon-investmen...
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...