Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
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
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
We explore the problem of resolving the second person English pronoun you in multi-party dialogue, using a combination of linguistic and visual features. First, we distinguish gen...
In this work, we propose a multi-class classification strategy based on Fisher kernels. Fisher kernels combine the powers of discriminative and generative classifiers by mapping v...