We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set ...
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Automatic classification of the aesthetic content of a picture is one of the challenges in the emerging discipline of computational aesthetics. Any suitable solution must cope wit...
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication...