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About Quantum Recommendation Systems: Iordanis Kerenidis Anupam Prakash September 23, 2016
This document proposes a quantum algorithm for recommendation systems that runs in polylogarithmic time in the dimensions of the preference matrix, which is faster than classical algorithms. It assumes the preference matrix has a good low-rank approximation, and classical algorithms reconstruct this matrix to make recommendations. The quantum algorithm instead samples efficiently from the approximated matrix without full reconstruction. This provides a quantum machine learning algorithm for a real-world application.
Detailed Information
| Author: | ['Cazimir Bostan'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 22 |
| Language: | English |
| Format: | |
| Price: | FREE |
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