Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...