kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper we introduce the new task of social event extraction from text. We distinguish two broad types of social events depending on whether only one or both parties are awa...
In this paper, we analyze the impact of different automatic annotation methods on the performance of supervised approaches to the complex question answering problem (defined in th...
—Emerging applications of computer vision and pattern recognition in mobile devices and networked computing require the development of resourcelimited algorithms. Linear classifi...