Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
In this paper, an efficient global algorithm for vectorizing line drawings is presented. It first extracts a seed segment of a graphic entity from a raster image to obtain its dir...
Jiqiang Song, Feng Su, Jibing Chen, Chiew-Lan Tai,...
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...