We present a novel weighted approach for shrinkage functions learning in image denoising. The proposed approach optimizes the shape of the shrinkage functions and maximizes denois...
This paper introduces a simple evaluation function for multiple instance learning that admits an optimistic pruning strategy. We demonstrate comparable results to state of the art...
The learning in a niche based learning classifier system depends both on the complexity of the problem space and on the number of available actions. In this paper, we introduce a ...
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
Abstract. We study predicate selection functions (also known as splitting rules) for structural decision trees and propose two improvements to existing schemes. The first is in cl...