http://arxiv.org/abs/1406.7536
The incredible variety of galaxy shapes cannot be summarized by human defined discrete classes of shapes without causing a possibly large loss of information. Dictionary learning and sparse coding allow us to reduce the high dimensional space of shapes into a manageable low dimensional continuous vector space. Statistical inference can be done in the reduced space via probability distribution estimation and manifold estimation.
G. Vinci, P. Freeman, J. Newman, et. al.
Tue, 1 Jul 14
57/70
Comments: 4 pages, 3 figures, Statistical Challenges in 21st Century Cosmology, Proceedings IAU Symposium No. 306, 2014