We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
One important aspect of motivation is engagement. In order to learn, students need to be engaged in the learning activities. However, that does not always happen due to various fac...
Treemaps are a well-known method for the visualization of attributed hierarchical data. Previously proposed Treemap layout algorithms are limited to rectangular shapes, which caus...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...