Abstract. For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and s...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
The increasing complexities of modern networks coupled with the popularity of multimedia applications have placed higher demands on network managers. This paper reviews the main r...
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...