This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
A method is proposed for semiparametric estimation where parametric and nonparametric criteria are exploited in density estimation and unsupervised learning. This is accomplished ...
- Many proteins contain a signal sequence at their COOH-terminus recognized by glycosylphosphatidylinositol (GPI) anchor and attached on the membrane. Experimental result suggests ...
Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The search is guided by a so-called utility function...