Scalable low-rank tensor learning for spatiotemporal traffic data imputation (2020-08-07T00:00:00.000000Z)

TL;DR

A scalable tensor learning model based on the existing framework of Low-Rank Tensor Completion, which is well-suited for spatiotemporal traffic data that is characterized by multidimensional structure of location, and can achieve competitive accuracy with a significantly lower computational cost.

Authors

Lijun Sun

4 papers

N. Saunier

3 papers

Xinyu Chen

3 papers

Yixian Chen

1 papers

Scalable low-rank tensor learning for spatiotemporal traffic data imputation

TL;DR

Authors

References26 items

A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

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Nearest Neighbor Imputation for Survey Data

Chen would like to thank the Institute for Data Valorisation (IVADO) for providing the Ph.D. scholarship to support this study

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