delta-submodular work codes
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Updated
Jul 22, 2021 - MATLAB
delta-submodular work codes
A GPU accelerated Submodular Optimization toolkit.
Code for our AISTATS '22 paper: Improving Attribution Methods by Learning Submodular Functions.
Routines for submodular set function minimization
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Randomized Greedy Learning Under Full-bandit Feedback
Personalized knowledge graph summarization based on historical queries
Probabilistic Gas Leak Rate Estimation using Submodular Function Maximization with Routing Constraints
A partial Benders decomposition (PBD) for solving choice-based competitive facility location problems (CBCFLP)
A collection of optimization algorithms for maximizing unconstrained submodular set functions.
Non-Uniform Subset Selection for Active Learning in Structured Data
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html
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