We generalize the Winnow algorithm for learning disjunctions to learning subspaces of low rank. Subspaces are represented by symmetric projection matrices. The online algorithm ma...
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
This paper presents an original approach to modelling user’s information need in text filtering environment. This approach relies on a specific novelty detection model which a...