This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
With the advent of open source software repositories the data available for defect prediction in source files increased tremendously. Although traditional statistics turned out t...
We present automated, real-time models built with machine learning algorithms which use videotapes of subjects' faces in conjunction with physiological measurements to predic...
Jeremy N. Bailenson, Emmanuel D. Pontikakis, Iris ...
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
In recent years, extraction of temporal relations for events that express sentiments has drawn great attention of the Natural Language Processing (NLP) research communities. In thi...