用干扰信号让自编码器隐空间逼近标准高斯分布。
Adversarial Jamming for Autoencoder Distribution Matching
- 用对抗性干扰作为辅助目标，正则化隐空间分布。
- 隐空间后验匹配度接近标准VAE与Wasserstein VAE。
- 方法可扩展至其他目标分布，适合生成模型研究者。
我们提出利用对抗性无线干扰来正则化自编码器的隐空间，使其匹配对角高斯分布。在最小化均方误差失真的情况下，干扰者试图破坏通过对抗信道传输的高斯源的恢复。现有理论结果表明，该最小最大博弈（包含编码器、解码器和对抗干扰者）的鞍点解为干扰者输出对角高斯噪声。我们以此为灵感，提出一种新方法：利用干扰作为辅助目标，促使聚合隐空间后验匹配对角高斯分布。实验表明，该方法实现的分布匹配效果与标准变分自编码器（VAE）及瓦瑟斯坦自编码器（Wasserstein Autoencoder）相当。该方法还可推广至其他隐空间分布。
原文摘要 · Abstract (English)
We propose the use of adversarial wireless jamming to regularise the latent space of an autoencoder to match a diagonal Gaussian distribution. We consider the minimisation of a mean squared error distortion, where a jammer attempts to disrupt the recovery of a Gaussian source encoded and transmitted over the adversarial channel. A straightforward consequence of existing theoretical results is the fact that the saddle point of a minimax game - involving such an encoder, its corresponding decoder, and an adversarial jammer - consists of diagonal Gaussian noise output by the jammer. We use this result as inspiration for a novel approach to distribution matching in the latent space, utilising jamming as an auxiliary objective to encourage the aggregated latent posterior to match a diagonal Gaussian distribution. Using this new technique, we achieve distribution matching comparable to standard variational autoencoders and to Wasserstein autoencoders. This approach can also be generalised to other latent distributions.
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