Performance addresses the generalization capability of a learning machine on randomly chosen samples that are not included in a training set.
Efficiency deals with the complexity of a learning machine in both space and time.
As these two issues are general to various learning machines and learning approaches, we focus on a special type of adaptive learning systems with a neural architecture. An optimal algorithm for Monte Carlo estimation - Dagum, Karp et al. Doc 5 IEEE Transactions on Neural Networks - Ji, Ma et al. A cost function for internal representations - Krough, Thorberaso et al.