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arXiv · 1911.04060

Invariant Representations through Adversarial Forgetting

Ayush Jaiswal·Daniel Moyer·Greg Ver Steeg·Wael AbdAlmageed·Premkumar Natarajan
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Abstract

We propose a novel approach to achieving invariance for deep neural networks in the form of inducing amnesia to unwanted factors of data through a new adversarial forgetting mechanism. We show that the forgetting mechanism serves as an information-bottleneck, which is manipulated by the adversarial training to learn invariance to unwanted factors. Empirical results show that the proposed framework achieves state-of-the-art performance at learning invariance in both nuisance and bias settings on a diverse collection of datasets and tasks.

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Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan. 2019-11-11. Invariant Representations through Adversarial Forgetting. https://arxiv.org/abs/1911.04060

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