Imagine two identical people receive exactly the same training on how to classify certain objects. Perhaps surprisingly, we show that one can then manipulate them into classifying...
Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timo...
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Adaptive Hypermedia (AH) can offer a richer learning experience, tailored to students’ needs. However, authoring of AH is complex. Several models and systems have been developed...
Maurice Hendrix, Alexandra I. Cristea, Craig Stewa...