  We introduce ADMM-pruned Compressive AutoEncoder (CAE-ADMM) that uses
Alternative Direction Method of Multipliers (ADMM) to optimize the trade-off
between distortion and efficiency of lossy image compression. Specifically,
ADMM in our method is to promote sparsity to implicitly optimize the bitrate,
different from entropy estimators used in the previous research. The
experiments on public datasets show that our method outperforms the original
CAE and some traditional codecs in terms of SSIM/MS-SSIM metrics, at reasonable
inference speed.
