We investigate the problem of variable-length compression with random access for stationary and ergodic sources, wherein short substrings of the raw file can be extracted from the compressed file without decompressing the entire file. It is possible to design compressors for sequences of length n that achieve compression rates close to the entropy rate of the source, and still be able to extract individual source symbols in time θ(1) under the word-RAM model. In this article, we analyze a simple well-known approach used for compression with random access. We theoretically show that this is suboptimal, and design two simple compressors that simultaneously achieve entropy rate and constant-time random access. We then propose dictionary compre...
Many results in statistics and information theory are asymptotic in nature, with the implicit assump...
This work1 deals with the fundamental limits of strictly-lossless variable-length compression of kno...
Parallel algorithms for lossless data compression via dictionary compression using optimal, longest ...
We examine the compression-complexity trade-off of lossy compression algorithms that are based on a ...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
The compression-complexity trade-off of lossy compression algorithms that are based on a random code...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
We address parallel and high-speed lossless data compression. Data compression attempts to reduce th...
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but unt...
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but unt...
Many results in statistics and information theory are asymptotic in nature, with the implicit assump...
This work1 deals with the fundamental limits of strictly-lossless variable-length compression of kno...
Parallel algorithms for lossless data compression via dictionary compression using optimal, longest ...
We examine the compression-complexity trade-off of lossy compression algorithms that are based on a ...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
The compression-complexity trade-off of lossy compression algorithms that are based on a random code...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
A well-known fact in the field of lossless text compression is that high-order entropy is a weak mod...
We address parallel and high-speed lossless data compression. Data compression attempts to reduce th...
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but unt...
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but unt...
Many results in statistics and information theory are asymptotic in nature, with the implicit assump...
This work1 deals with the fundamental limits of strictly-lossless variable-length compression of kno...
Parallel algorithms for lossless data compression via dictionary compression using optimal, longest ...