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Found 4 papers, 2 papers with code
Fairness in Streaming Submodular Maximization over a Matroid Constraint
Streaming submodular maximization is a natural model for the task of selecting a representative subset from a large-scale dataset.
Efficient and Local Parallel Random Walks
Random walks are a fundamental primitive used in many machine learning algorithms with several applications in clustering and semi-supervised learning.
Streaming Belief Propagation for Community Detection
The community detection problem requires to cluster the nodes of a network into a small number of well-connected "communities".
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
Submodular maximization has become established as the method of choice for the task of selecting representative and diverse summaries of data.
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