Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
In learning from examples it is often useful to expand an attribute-vector representation by intermediate concepts. The usual advantage of such structuring of the learning problemi...
Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Brat...
A new emerging field, that of visual stylometry of art, proposes to apply image analysis and machine learning tools to high-resolution digital images of artwork in order to assis...
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...