KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
On the influence of the kernel on the consistency of support vector machines
The Journal of Machine Learning Research
Rademacher and gaussian complexities: risk bounds and structural results
The Journal of Machine Learning Research
The Journal of Machine Learning Research
On Constraint Sampling in the Linear Programming Approach to Approximate Dynamic Programming
Mathematics of Operations Research
Unifying divergence minimization and statistical inference via convex duality
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Probability density estimation from optimally condensed data samples
IEEE Transactions on Pattern Analysis and Machine Intelligence
A PAC-bayes bound for tailored density estimation
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
The Journal of Machine Learning Research
Inferring a graph from path frequency
Discrete Applied Mathematics
Robust kernel density estimation
The Journal of Machine Learning Research
Information estimators for weighted observations
Neural Networks
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Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distributions into a reproducing kernel Hilbert space, and performing moment matching in that space. This allows us to tailor density estimators to a function class of interest (i.e., for which we would like to compute expectations). We show our density estimation approach is useful in applications such as message compression in graphical models, and image classification and retrieval.