No abstract

No abstract

We present a novel system providing summaries for Computer Science publications. Through a qualitative user study, we identified the most valuable scenarios for discovery, exploration and understanding of scientific documents. Based on these findings, we built a system that retrieves and summarizes scientific documents for a given information need, either in form of a free-text query or by choosing categorized values such as scientific tasks, datasets and more. Our system ingested 270,000 papers, and its summarization module aims to generate concise yet detailed summaries. We validated our approach with human experts.

No abstract

This paper deals with uncertain conic quadratic constraints. An approximate robust counterpart is formulated for the case where both sides of the constraint depend on the same perturbations, and the perturbations belong to an uncertainty set which is an intersection of ellipsoids. Examples to problems in which such constraints occur are presented and solved.