Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
26
Zitationen
3
Autoren
2019
Jahr
Abstract
The bits-back argument suggests that latent variable models can be turned into lossless compression schemes. Translating the bits-back argument into efficient and practical lossless compression schemes for general latent variable models, however, is still an open problem. Bits-Back with Asymmetric Numeral Systems (BB-ANS), recently proposed by Townsend et al. (2019), makes bits-back coding practically feasible for latent variable models with one latent layer, but it is inefficient for hierarchical latent variable models. In this paper we propose Bit-Swap, a new compression scheme that generalizes BB-ANS and achieves strictly better compression rates for hierarchical latent variable models with Markov chain structure. Through experiments we verify that Bit-Swap results in lossless compression rates that are empirically superior to existing techniques. Our implementation is available at this https URL.
Ähnliche Arbeiten
Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm
1977 · 49.510 Zit.
2022 · 19.552 Zit.
Inference from Iterative Simulation Using Multiple Sequences
1992 · 16.595 Zit.
Auto-Encoding Variational Bayes
2013 · 15.586 Zit.
Understanding the difficulty of training deep feedforward neural networks
2010 · 12.676 Zit.