A Sparse graph code is a code which is represented by a sparse graph. Any linear code can be represented as a graph, where there are two sets of nodes...

a flexible design method that is based on sparse Tanner graphs (specialized bipartite graphs). LDPC codes were originally conceived by Robert G. Gallager...

In graph theory, an expander graph is a sparse graph that has strong connectivity properties, quantified using vertex, edge or spectral expansion. Expander...

Pareto principle Ragged matrix Single-entry matrix Skyline matrix Sparse graph code Sparse file Harwell-Boeing file format Matrix Market exchange formats...

Outerplanar graph Random graph Regular graph Scale-free network Snark (graph theory) Sparse graph Sparse graph code Split graph String graph Strongly regular...

Gallager code, as the archetype for sparse graph codes LT code, which is a near-optimal rateless erasure correcting code (Fountain code) m of n codes Nordstrom-Robinson...

This is a list of algebraic coding theory topics....

These methods focus on the encoding of text as either dense or sparse vectors. Sparse vectors, which encode the identity of a word, are typically dictionary-length...

A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key...

this sense, planar graphs are sparse graphs, in that they have only O(v) edges, asymptotically smaller than the maximum O(v2). The graph K3,3, for example...

In graph theory, graph coloring is a methodic assignment of labels traditionally called "colors" to elements of a graph. The assignment is subject to certain...

the language of linear algebra. GraphBLAS is built upon the notion that a sparse matrix can be used to represent graphs as either an adjacency matrix or...

In graph theory and computer science, an adjacency matrix is a square matrix used to represent a finite graph. The elements of the matrix indicate whether...

science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within...

{\displaystyle \Theta (|E|+|V|^{2})=\Theta (|V|^{2})} . For sparse graphs, that is, graphs with far fewer than | V | 2 {\displaystyle |V|^{2}} edges, Dijkstra's...

model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime...

of the longest induced path in a graph has sometimes been called the detour number of the graph; for sparse graphs, having bounded detour number is equivalent...

problem in a weighted, directed graph Johnson's algorithm: all pairs shortest path algorithm in sparse weighted directed graph Transitive closure problem:...

algorithms have been developed for factorizing large sparse matrices. These algorithms attempt to find sparse factors L and U. Ideally, the cost of computation...

Polyspace PVS-Studio SLAM project Sparse SonarQube Splint Understand Visual Studio Axivion Suite (Bauhaus) Code Dx CodeScene CodeQL Coverity Kiuwan Klocwork...

collection of graphs used as benchmarks for the challenge, which is publicly available. Planar graphs, and other families of sparse graphs, have been discussed...

concise code that is easy to understand and debug, while being well suited for irregular algorithms, such as algorithms on trees, graphs or sparse matrices...

Coates and Ng note that certain variants of k-means behave similarly to sparse coding algorithms. In a comparative evaluation of unsupervised feature learning...

in advance Sparse conditional constant propagation – range-check some values, allowing tests to predict the most likely branch Dead-code elimination...

and graph theory. He is a professor of mathematics at the University of Haifa. He is a recipient of the Nerode Prize for his work on color-coding,[A]...

on trees, preprocess a graph to enable constant-time LCA queries. The problem of LCA existence can be solved optimally for sparse DAGs by means of an O(|V||E|)...

propagation known as sparse conditional constant propagation can more accurately propagate constants and simultaneously remove dead code. Constant folding...

operator, defined so that it has meaning on a graph or a discrete grid. For the case of a finite-dimensional graph (having a finite number of edges and vertices)...

Sparse distributed memory (SDM) is a mathematical model of human long-term memory introduced by Pentti Kanerva in 1988 while he was at NASA Ames Research...

explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. For instance...