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06/05/2019
Unbiased estimators for the variance of MMD estimators
The maximum mean discrepancy (MMD) is a kernel-based distance between pr...
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05/29/2018
On gradient regularizers for MMD GANs
We propose a principled method for gradient-based regularization of the ...
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01/04/2018
Demystifying MMD GANs
We investigate the training and performance of generative adversarial ne...
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05/23/2017
Efficient and principled score estimation with Nyström kernel exponential families
We propose a fast method with statistical guarantees for learning an exp...
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05/11/2017
Bayesian Approaches to Distribution Regression
Distribution regression has recently attracted much interest as a generi...
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02/09/2017
Fixing an error in Caponnetto and de Vito (2007)
The seminal paper of Caponnetto and de Vito (2007) provides minimax-opti...
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11/14/2016
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
We propose a method to optimize the representation and distinguishabilit...
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11/13/2015
Deep Mean Maps
The use of distributions and high-level features from deep architecture ...
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09/24/2015
Linear-time Learning on Distributions with Approximate Kernel Embeddings
Many interesting machine learning problems are best posed by considering...
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06/09/2015
On the Error of Random Fourier Features
Kernel methods give powerful, flexible, and theoretically grounded appro...
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02/01/2012