Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
Community Question Answering has emerged as a popular and effective paradigm for a wide range of information needs. For example, to find out an obscure piece of trivia, it is now ...
Online boosting is one of the most successful online learning algorithms in computer vision. While many challenging online learning problems are inherently multi-class, online boo...
Amir Saffari, Martin Godec, Thomas Pock, Christian...