Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
Over the last few years, blogs (web logs) have gained massive popularity and have become one of the most influential web social media in our times. Every blog post in the Blogosph...
We present a system for personalized tag suggestion for Flickr: While the user is entering/selecting new tags for a particular picture, the system is suggesting related tags to he...