In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
Neurons in the nervous system display a wide variety of plasticity processes. Among them are covariance based rules and homeostatic plasticity. By themselves, the first ones tend...
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffe...