The complexity, variation, and change of human languages makes evident the importance of representation and learning in the acquisition and evolution of language. For example, anal...
Yoosook Lee, Travis C. Collier, Gregory M. Kobele,...
Abstract. This paper proposes a novel algorithm based on informax for postnonlinear blind source separation. The demixing system culminates to a neural network with sandwiched stru...
Chunhou Zheng, Deshuang Huang, Zhan-Li Sun, Li Sha...
This paper describes a new automatic method for Japanese predicate argument structure analysis. The method learns relevant features to assign case roles to the argument of the tar...
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...