We introduce a new genetic operator, Reduction, that rectifies decision trees not correct syntactically and at the same time removes the redundant sections within, while preservin...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Abstract. The sparse representation has been widely used in many areas and utilized for visual tracking. Tracking with sparse representation is formulated as searching for samples ...
Baiyang Liu, Lin Yang, Junzhou Huang, Peter Meer, ...
When releasing microdata for research purposes, one needs to preserve the privacy of respondents while maximizing data utility. An approach that has been studied extensively in re...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...