Efficient and Compact Representations of Some Non-Canonical Prefix-Free Codes
May 21, 2016 Β· Declared Dead Β· π SPIRE
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Antonio FariΓ±a, Travis Gagie, Szymon Grabowski, Giovanni Manzini, Gonzalo Navarro, Alberto OrdΓ³Γ±ez
arXiv ID
1605.06615
Category
cs.DS: Data Structures & Algorithms
Citations
5
Venue
SPIRE
Last Checked
4 months ago
Abstract
For many kinds of prefix-free codes there are efficient and compact alternatives to the traditional tree-based representation. Since these put the codes into canonical form, however, they can only be used when we can choose the order in which codewords are assigned to symbols. In this paper we first show how, given a probability distribution over an alphabet of $Ο$ symbols, we can store an optimal alphabetic prefix-free code in $\Oh{Ο\log L}$ bits such that we can encode and decode any codeword of length $\ell$ in $\Oh{\min (\ell, \log L)}$ time, where $L$ is the maximum codeword length. With $\Oh{2^{L^Ξ΅}}$ further bits, for any constant $Ξ΅>0$, we can encode and decode $\Oh{\log \ell}$ time. We then show how to store a nearly optimal alphabetic prefix-free code in \(o (Ο)\) bits such that we can encode and decode in constant time. We also consider a kind of optimal prefix-free code introduced recently where the codewords' lengths are non-decreasing if arranged in lexicographic order of their reverses. We reduce their storage space to $\Oh{Ο\log L}$ while maintaining encoding and decoding times in $\Oh{\ell}$. We also show how, with $\Oh{2^{Ξ΅L}}$ further bits, we can encode and decode in constant time. All of our results hold in the word-RAM model.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted