We present a unified approach to locality optimization that employs both data and control transformations. Data transformations include changing the array layout in memory. Contr...
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
In this paper, we present a trainable approach to discriminate between machine-printed and handwritten text. An integrated system able to localize text areas and split them in tex...
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Abstract. In this paper, we use supervised machine learning to automatically identify the problem localization of peer-review feedback. Using five features extracted via Natural L...