In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Business users and analysts commonly use spreadsheets and 2D plots to analyze and understand their data. On-line Analytical Processing (OLAP) provides these users with added flexi...