Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
This paper address the problem of entity linking. Specifically, given an entity mentioned in unstructured texts, the task is to link this entity with an entry stored in the existi...