Annotating training data for event extraction is tedious and labor-intensive. Most current event extraction tasks rely on hundreds of annotated documents, but this is often not en...
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Abstract: Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several predefined topics simultaneously. In mul...
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a lo...
Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone, ...