Lossless Compression via Chained Lightweight Neural Predictors with Information Inheritance
This paper is dedicated to lossless data compression with probability estimation using neural networks. First, we propose a probability estimation architecture based on a chain of neural predictors, so that each unit of the chain is defined as a neural network with the minimum possible number of weights, which is sufficient for efficient compression of data generated by Markov sources of a given order. We show that this architecture allows us to minimize the overall number of weights participating in the probability estimation process depending on the statistical properties of the input data. Second, in order to improve compression efficiency, we introduce an information inheritance mecha...
| Authors | Yuriy Kim, Evgeny Belyaev |
|---|---|
| Primary category | cs.IT |
| Published | 16 April 2026 |
| Last updated at source | 16 April 2026 |
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