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Found 6 papers, 5 papers with code
Targeted Branching for the Maximum Independent Set Problem
Some of the most successful algorithms for this problem are based on the branch-and-bound or branch-and-reduce paradigms.
Data Structures and Algorithms
Boosting Data Reduction for the Maximum Weight Independent Set Problem Using Increasing Transformations
A key feature of our work is that some transformation rules can increase the size of the input.
Communication-free Massively Distributed Graph Generation
Analyzing massive complex networks yields promising insights about our everyday lives.
Distributed, Parallel, and Cluster Computing Data Structures and Algorithms Social and Information Networks
Efficient Random Sampling - Parallel, Vectorized, Cache-Efficient, and Online
We consider the problem of sampling $n$ numbers from the range $\{1,\ldots, N\}$ without replacement on modern architectures.
Data Structures and Algorithms Distributed, Parallel, and Cluster Computing Mathematical Software G.4; G.3; G.2
Finding Near-Optimal Independent Sets at Scale
To avoid this problem, we recursively choose vertices that are likely to be in a large independent set (using an evolutionary approach), then further kernelize the graph.
Graph Partitioning for Independent Sets
The core innovations of the algorithm are very natural combine operations based on graph partitioning and local search algorithms.
