Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
In this theoretical contribution we provide mathematical proof that two of the most important classes of network learning - correlation-based differential Hebbian learning and rew...
Christoph Kolodziejski, Bernd Porr, Minija Tamosiu...
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Poor literacy remains a decisive barrier to the economic empowerment of many people in the developing world. Of particular importance is literacy in a widely spoken "world la...
Matthew Kam, Divya Ramachandran, Varun Devanathan,...