The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
Given their autonomy, flexibility and large range of functionality, wireless sensor networks can be used as an effective and discrete means for monitoring data in many domains. T...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Owing to the stochastic nature of discrete processes such as photon counts in imaging, real-world data measurements often exhibit heteroscedastic behavior. In particular, time ser...
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...