'International workshop on clustering high-dimensional data', Naples, Italy
One of the strongest problems affecting current machine learning techniques is dataset dimensionality. In many applications to real world problems, data may come from anywhere from a few dozen to many thousands of dimensions.
Such high-dimensional data spaces are often encountered in areas such as medicine or biology, where technology can produce a large number of measurements at once. This can make learning problems hard to manage.
The event will be a forum for stakeholders to examine current approaches towards clustering high-dimensional data. Topics are set to include:
- relational clustering;
- data reduction using rough and fuzzy sets;
- subspace clustering;
- projected clustering;
- correlation clustering;
- biclustering/co-clustering;
- clustering ensembles;
- multi-view clustering.For further information, please visit: http://sites.google.com/site/chdd12naples(opens in new window)