Real-word applications often involve a binary hypothesis testing problem with one of the two hypotheses ill-defined and hard to be characterized precisely by a single measure. In ...
For the tasks of classification, two types of patterns can generate problems: ambiguous patterns and outliers. Furthermore, it is possible to separate classification algorithms in...
Jonathan Milgram, Mohamed Cheriet, Robert Sabourin
Choosing the appropriate type of video input is an important issue for any vision-based system and the right decision must take into account the specific requirements of the inten...
We present a novel feature screening algorithm by deriving relevance measures from the decision boundary of Support Vector Machines. It alleviates the "independence" assu...
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...