In this paper we compared the performance of the Automatic Data Reduction System (ADRS) and principal component analysis (PCA) as a preprocessor to artificial neural networks (ANN...
Nicholas Navaroli, David Turner, Arturo I. Concepc...
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
Abstract. A previous paper [2] presented a model (UCPF-HC) of the hippocampus as a unitary coherent particle filter, which combines the classical hippocampal roles of associative m...
We present an unsupervised model for joint phrase alignment and extraction using nonparametric Bayesian methods and inversion transduction grammars (ITGs). The key contribution is...
Graham Neubig, Taro Watanabe, Eiichiro Sumita, Shi...
In this paper, we show how we can learn to select good words for a document title. We view the problem of selecting good title words for a document as a variant of an Information ...