Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
This paper examines agent-based systems designed for a variety of human learning tasks. These are typically split into two areas: "training", which generally refers to a...
In this paper we introduce a method for computing fitness in evolutionary learning systems based on NVIDIA’s massive parallel technology using the CUDA library. Both the match ...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
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...