Many tasks of information extraction or natural language processing have a property that the data naturally consist of several views--disjoint subsets of features. Specifically, a ...
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
—This paper proposes a method of learning a similarity matrix from pairwise constraints for interactive clustering. The similarity matrix can be learned by solving an optimizatio...
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
— Classic adaptive control methods for handling varying loads rely on an analytically derived model of the robot’s dynamics. However, in many situations, it is not feasible or ...