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Found 3 papers, 0 papers with code
Efficient inference of overlapping communities in complex networks
We discuss two views on extending existing methods for complex network modeling which we dub the communities first and the networks first view, respectively.
Predicting clicks in online display advertising with latent features and side-information
We review a method for click-through rate prediction based on the work of Menon et al. [11], which combines collaborative filtering and matrix factorization with a side-information model and fuses the outputs to proper probabilities in [0, 1].
Dimensionality reduction for click-through rate prediction: Dense versus sparse representation
In this work, we propose to use dimensionality reduction of the user-website interaction graph in order to produce simplified features of users and websites that can be used as predictors of clickthrough rate.
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