《TABLE IVTIME COST OF EACH TESTED MODEL TO ACHIEVE THE LOWESTPREDICTION ERROR IN THE EXPERIMENTS (IN

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《Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial Applications》

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5) To summarize，when compared with state-of-the-art LF models，the proposed RLF and BRLF models achieve significantly higher computational efficiency as well as competitive prediction accuracy for missing data.Hence，they provide us with a novel，effective，and highly efficient approach to LF analysis of HiDS matrices.