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cs.LG2013★ 8 cited
Semi-supervised Eigenvectors for Large-scale Locally-biased Learning
Toke J. Hansen, Michael W. Mahoney
In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to per…
cs.AI2013
Integrating Probabilistic Rules into Neural Networks: A Stochastic EM Learning Algorithm
Gerhard Paass
The EM-algorithm is a general procedure to get maximum likelihood estimates if part of the observations on the variables of a network are missing. In this paper a stochastic versio…
cs.LG2013★ 2.1k cited
Probabilistic Latent Semantic Analysis
Thomas Hofmann
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two-mode and co-occurrence data, which has applications in information retrieval and fil…