We introduce a stochastic grammatical channel model for machine translation, that synthesizes several desirable characteristics of both statistical and grammatical machine transla...
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites th...
This work explores the application of clustering methods for grouping structurally similar XML documents. Modeling the XML documents as rooted ordered labeled trees, we apply clust...
Theodore Dalamagas, Tao Cheng, Klaas-Jan Winkel, T...