Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
Abstract. This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these ...
Link prediction is a key technique in many applications such as recommender systems, where potential links between users and items need to be predicted. A challenge in link predic...
The first major contribution of this paper is a robust method to learn the photometric mapping between the overlapping portions of two registered images acquired either under dif...
Abstract. We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at appl...