We propose a view-constrained latent variable model for multi-view facial expression classification. In this model, we first learn a discriminative manifold shared by multiple views of facial expressions, followed by the expression classification in the shared manifold. For learning, we use the expression data from multiple views, however, the inference is performed using the data from a single...

This paper describes Scorpio, the ILLCUvA Adaptation System submitted to the IT-DOMAIN translation task at WMT 2016, which participated with the language pair of English-Dutch. This system consolidates the ideas in our previous work on latent variable models for adaptation, and demonstrates their effectiveness in a competitive setting.

We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1],[2], a probabilistically defined latent variable model which takes the alternative approach of marginalizing the parameters and optimizing the latent variables; we optimize a latent variable set for each dataset, which preser...

Certain causal models involving unmea­ sured variables induce no independence constraints among the observed variables but imply, nevertheless, inequality con­ straints on the observed distribution. This paper derives a general formula for such in­ equality constraints as induced by instru­ mental variables, that is, exogenous vari­ ables that directly affect some variables but not all. With th...

We propose models for semantic orientations of phrases as well as classification methods based on the models. Although each phrase consists of multiple words, the semantic orientation of the phrase is not a mere sum of the orientations of the component words. Some words can invert the orientation. In order to capture the property of such phrases, we introduce latent variables into the models. T...