Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
This paper proposes a mechanism of noise tolerance for reinforcement learning algorithms. An adaptive agent that employs reinforcement learning algorithms may receive and accumula...
Richardson Ribeiro, Alessandro L. Koerich, Fabr&ia...
Windowing has been proposed as a procedure for efficient memory use in the ID3 decision tree learning algorithm. However, it was shown that it may often lead to a decrease in perf...
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large m...