Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
—Previous studies have demonstrated that document clustering performance can be improved significantly in lower dimensional linear subspaces. Recently, matrix factorization base...
We provide a reformulation of the constraint hierarchies (CHs) framework based on the notion of error indicators. Adapting the generalized view of local consistency in semiring-ba...
Stefano Bistarelli, Philippe Codognet, Kin Chuen H...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...