We propose a novel 1 2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard 1-norm inverse solver, the proposed sparse distributed inverse solve...
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
With a rich variety of forms and types, digital resources are complex data objects. They grows fast in volume on the Web, but hard to be classified efficiently. The paper presents ...
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...
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...