We address the problem of labeling individual datapoints given some knowledge about (small) subsets or groups of them. The knowledge we have for a group is the likelihood value fo...
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
We present a class of models that are discriminatively trained to directly map from the word content in a query-document or documentdocument pair to a ranking score. Like Latent Se...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Large 0-1 datasets arise in various applications, such as market basket analysis and information retrieval. We concentrate on the study of topic models, aiming at results which in...