In a paper published on the preprint server Arxiv.org, researchers at IBM propose StarNet, an end-to-end trainable image classifier that’s able to localize what it believes to be the key regions supporting its predictions. Besides addressing the task of visual classification, StarNet supports the task of weakly supervised few-shot object detection, such that only a small amount of noisy data is…

In a new study, researchers at Amazon describe a technique that factors in information about knowledge graphs to perform entity alignment, which entails determining which elements of different graphs refer to the same “entities” (which might be anything from products to song titles). The idea is to improve computational efficiency while at the same time improving performance, speeding up…