The phenomenal growth of video on the web and the increasing sparseness of meta information associated with it forces us to look for signals from the video content for search/info...
Ming Zhao 0003, Jay Yagnik, Hartwig Adam, David Ba...
Although mixed-membership models have achieved great success in unsupervised learning, they have not been widely applied to classification problems. In this paper, we propose a f...
Time on task is an important predictor for how much students learn. However, students must be focused on their learning for the time invested to be productive. Unfortunately, stude...
Abstract. People-centric sensor-based applications targeting mobile device users offer enormous potential. However, learning inference models in this setting is hampered by the lac...
Nicholas D. Lane, Hong Lu, Shane B. Eisenman, Andr...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...