Sutherland, DJ;
Tung, H-Y;
Strathmann, H;
De, S;
Ramdas, A;
Smola, A;
Gretton, A;
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy.
In:
Proceedings of the 5th International Conference on Learning Representations (ICLR 2017).
International Conference on Learning Representations: Toulon, France.
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Abstract
We propose a method to optimize the representation and distinguishability of samples from two probability distributions, by maximizing the estimated power of a statistical test based on the maximum mean discrepancy (MMD). This optimized MMD is applied to the setting of unsupervised learning by generative adversarial networks (GAN), in which a model attempts to generate realistic samples, and a discriminator attempts to tell these apart from data samples. In this context, the MMD may be used in two roles: first, as a discriminator, either directly on the samples, or on features of the samples. Second, the MMD can be used to evaluate the performance of a generative model, by testing the model's samples against a reference data set. In the latter role, the optimized MMD is particularly helpful, as it gives an interpretable indication of how the model and data distributions differ, even in cases where individual model samples are not easily distinguished either by eye or by classifier.
Type: | Proceedings paper |
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Title: | Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy |
Event: | 5th International Conference on Learning Representations (ICLR 2017) |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://openreview.net/forum?id=HJWHIKqgl |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit |
URI: | https://discovery.ucl.ac.uk/id/eprint/1567005 |
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