The need for efficient decentralized recommender systems has been appreciated for some time, both for the intrinsic advantages of decentralization and the necessity of integrating...
Anne-Marie Kermarrec, Vincent Leroy, Afshin Moin, ...
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-labe...
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
Eliciting user preferences for large datasets and creating rankings based on these preferences has many practical applications in community-based sites. This paper gives a new met...