Neural-Kernelized Conditional Density Estimation

5 Jun 2018Hiroaki SasakiAapo Hyvärinen

Conditional density estimation is a general framework for solving various problems in machine learning. Among existing methods, non-parametric and/or kernel-based methods are often difficult to use on large datasets, while methods based on neural networks usually make restrictive parametric assumptions on the probability densities... (read more)

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