We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
— There are various scenarios where finding the most similar expression is the requirement rather than just classifying one, for example, facial expression transfer and facial e...
Within the taxonomy of feature extraction methods, recently the Wrapper approaches lost some popularity due to the associated computational burden, compared to Embedded or Filter m...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
Clinical medical records contain a wealth of information, largely in free-text form. Means to extract structured information from free-text records is an important research endeav...
Xiaohua Zhou, Hyoil Han, Isaac Chankai, Ann Prestr...
This paper describes a novel Bayesian approach to unsupervised topic segmentation. Unsupervised systems for this task are driven by lexical cohesion: the tendency of wellformed se...