Can reordering data improve compression ratios?

May 24, 2011 ... My opinion will be, first decide whether you want to do a lossless compression or a lossy compression, then pick an algorithm to implement. Sep 19, 2019 ... Lossless compression for high-dimensional data · choosing a statistical model that closely captures the underlying distribution of the input data ... The thesis proposes a lossless data compression technique in which the data is compressed by representing it as a set of parameters that can reproduce the ... Jan 1, 2013 ... ALACRITY: Analytics-Driven Lossless Data Compression for Rapid In-Situ Indexing, Storing, and Querying. In: Transactions on Large-Scale Data- ... Jan 22, 2019 ... Lossless data compression is the size reduction of a file, such that a decompression function can restore the original file exactly with no loss of data. This paper provides an Ontology-driven Data Cleaning mechanism, facilitating Lossless Healthcare Data Compression to efficiently compress healthcare data. This work presents a comparative analysis of data compression algorithms tailored for WSNs. It studies and enhances two adaptive lossless data compression ... Lossless compression techniques, as their name implies, involve no loss of information. If data have been losslessly compressed, the original data can be ... Aug 3, 2020 ... This Recommended Standard establishes a common framework and provides a common basis for a Lossless data compression algorithm applicable to ... Description. Data compression using neural networks. DeepZip: Lossless Data Compression using Recurrent Neural Networks. Requirements. GPU, nvidia-docker (or ...