The story of some early computer art drawings in 1965 is told. It is a story of randomness. Computer art is viewed here as the programming of classes of aesthetic objects. In the ...
While stochastic local search (SLS) techniques are very efficient in solving hard randomly generated propositional satisfiability (SAT) problem instances, a major challenge is to i...
We extend the classical single-task active learning (AL) approach. In the multi-task active learning (MTAL) paradigm, we select examples for several annotation tasks rather than f...
Roi Reichart, Katrin Tomanek, Udo Hahn, Ari Rappop...
Classifying what-type questions into proper semantic categories is found more challenging than classifying other types in question answering systems. In this paper, we propose to ...
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...