Recently, many approaches have been proposed for visual object category detection. They vary greatly in terms of how much supervision is needed. High performance object detection m...
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly o...
We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the applica...
Dong Zhang, Daniel Gatica-Perez, Samy Bengio, Iain...
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...