We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
A graph-based prior is proposed for parametric semi-supervised classification. The prior utilizes both labelled and unlabelled data; it also integrates features from multiple view...
Balaji Krishnapuram, David Williams, Ya Xue, Alexa...
This paper presents a staged series of artificial neural networks (ANNs) for phoneme recognition for text-to-speech applications. Contrary from much of the prior published literat...
Originally conceived as a "naive" baseline experiment using traditional n-gram language models as classifiers, the NCLEANER system has turned out to be a fast and lightw...
— This article presents a self-fuzzification method to enhance the settings of a Fuzzy Reasoning Classification adapted to the automated inspection of wooden boards. The supervis...
Emmanuel Schmitt, Vincent Bombardier, Patrick Char...