— Machine learning has made great progress during the last decades and is being deployed in a wide range of applications. However, current machine learning techniques are far fro...
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
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 ...
An additional platform for supporting learning in the same physical space in which it takes place, is now available owing to the continuous advancement of wireless and mobile tech...
Rosa G. J. Paredes, Hiroaki Ogata, Yoneo Yano, Ger...
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...