We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work...
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
A significant portion of the population is at risk of being excluded from online learning environments. People with learning and/or physically disabilities may be prevented from p...
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...