Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Abstract. There is a growing discrepancy between the creation of digital content and its actual employment and usefulness in a learning society. Technologies for recording lectures...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Humans can verify unknown parent-offspring and sibling pairs over unrelated subject pairs. A computational scheme to accomplish the task robustly, in the presence of challenges due...
Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to ...
Yanghai Tsin, Robert T. Collins, Visvanathan Rames...