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Relevance Proximity Graphs for Fast Relevance Retrieval
[article]
2019
arXiv
pre-print
In plenty of machine learning applications, the most relevant items for a particular query should be efficiently extracted, while the relevance function is based on a highly-nonlinear model, e.g., DNNs or GBDTs. Due to the high computational complexity of such models, exhaustive search is infeasible even for medium-scale problems. To address this issue, we introduce Relevance Proximity Graphs (RPG): an efficient non-exhaustive approach that provides a high-quality approximate solution for
arXiv:1908.06887v3
fatcat:ox5y64afwbdyzczyjec4fgqey4