Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate max...
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
Abstract The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temp...
Simon M. Stringer, G. Perry, Edmund T. Rolls, J. H...
We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...