We analyze why and how erroneous examples can be beneficially employed in learning mathematics. The `Why' addresses reasoning and attitudes that are rarely fostered in today&...
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...