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Fast and Private Submodular and k-Submodular Functions Maximization with Matroid Constraints
[article]
2020
arXiv
pre-print
The problem of maximizing nonnegative monotone submodular functions under a certain constraint has been intensively studied in the last decade, and a wide range of efficient approximation algorithms have been developed for this problem. Many machine learning problems, including data summarization and influence maximization, can be naturally modeled as the problem of maximizing monotone submodular functions. However, when such applications involve sensitive data about individuals, their privacy
arXiv:2006.15744v1
fatcat:vgjyf2cfuvecbhqtmxjzjfjv24