ILAA 2016 - Special session on Incremental learning algorithms and applications

This special sessions invites contributions from researchers in machine learning who develop incremental learning algorithms, as well as from researchers in applied fields, particularly robotics, who apply such algorithms to obtain superior performance or usability. The definition of incremental learning algorithms is notoriously unclear: It may include, but is not restricted to, algorithms that:
avoid catastrophic forgetting when retrained
can deal with non-stationary statistics: concept drift or concept shift
can treat "streaming" data and see each example only one
try to emulate biological architectures of life-long learning A particular focus lies on algorithms that rest efficient (w.r.t. time and memory) when faced with huge amounts of data, or data with large dimensionality, or both.