multimedia data, such as digital images, audio streams and motion video programs, show a richer structure than the simple, isolated data items. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly. Machine Learning for Multimedia Content Analysis introduces machine learning techniques that are very strong and effective for modeling spatial, temporal structure of multimedia data and to complete common tasks of multimedia content analysis. Thisvolume using a large number of figures to illustrate and visualize complex concepts, and provide insight into the many characteristics of the algorithm through an examination of their loss function and a direct comparison. Machine Learning for Multimedia Content Analysis is designed for academic and professional audience. The researchers will find this book a tool for applying machine learning techniques of multimedia content analysis.