In ensemble teacher learning, ensemble teachers have only uncertain information about the true teacher, and this information is given by an ensemble consisting of an infinite number of ensemble teachers whose variety is sufficiently rich. In this learning, a student learns from an ensemble teacher that is iteratively selected randomly from a pool of many ensemble teachers. An interesting point ...

In this paper, we provide uniform design and analysis framework for iterative learning control of a class of impulsive first-order distributed parameter systems in the time domain. In particular, P-type and D-type iterative learning controls with initial state learning are considered. We present convergence results for open-loop iterative learning schemes in the sense of the Lp-norm and λ-norm,...

This paper presents an original approach to neural modeling based on the idea of searching, with learning methods, for a synaptic learning rule which is biologically plausible, and yields networks that are able to learn to perform diicult tasks. The proposed method of automatically nding the learning rule relies on the idea of considering the synaptic modiication rule as a parametric function. ...

A hallmark of visual intelligence is the ability to extract relationships among objects. One form of extraction produces stimulus-specific knowledge (statistical learning). Another form produces stimulus-general principles (inductive learning). These two learning processes seem incompatible on the surface, but may be related on a deeper level. Here we examine how statistical learning and induct...