Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...
Component failure in large-scale IT installations is becoming an ever larger problem as the number of components in a single cluster approaches a million. In this paper, we presen...
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed to...
Vlad I. Morariu, Balaji Vasan Srinivasan, Vikas C....