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Efficient Parametric Projection Pursuit Density Estimation
Max Welling, Richard S. Zemel, Geoffrey E. Hinton
Product models of low dimensional experts are a powerful way to avoid the curse of dimensionality. We present the ``under-complete product of experts' (UPoE), where each expert mod…
Active Collaborative Filtering
Craig Boutilier, Richard S. Zemel, Benjamin Marlin
Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of onlin…
Fast Exact Inference for Recursive Cardinality Models
Daniel Tarlow, Kevin Swersky, Richard S. Zemel +2
Cardinality potentials are a generally useful class of high order potential that affect probabilities based on how many of D binary variables are active. Maximum a posteriori (MAP)…
Collaborative Filtering and the Missing at Random Assumption
Benjamin Marlin, Richard S. Zemel, Sam Roweis +1
Rating prediction is an important application, and a popular research topic in collaborative filtering. However, both the validity of learning algorithms, and the validity of stand…
Active Learning for Matching Problems
Laurent Charlin, Rich Zemel, Craig Boutilier
Effective learning of user preferences is critical to easing user burden in various types of matching problems. Equally important is active query selection to further reduce the am…
Flexible Priors for Exemplar-based Clustering
Daniel Tarlow, Richard S. Zemel, Brendan J. Frey
Exemplar-based clustering methods have been shown to produce state-of-the-art results on a number of synthetic and real-world clustering problems. They are appealing because they o…