In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
In this paper, we present a statistical model for detecting article errors, which Japanese learners of English often make in English writing. The model detects article errors base...
We now have incrementally-grown databases of text documents ranging back for over a decade in areas ranging from personal email, to news-articles and conference proceedings. While...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...