— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
Data sparseness is an ever dominating problem in automatic emotion recognition. Using artificially generated speech for training or adapting models could potentially ease this: t...
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Image annotations allow users to access a large image database with textual queries. There have been several studies on automatic image annotation utilizing machine learning techn...
Today's computer supported modelling environments could provide much more information about the users’ actions and problem solving processes than they usually store for late...